Claude Fable 5 Benchmarks: 80.3% SWE-Bench Pro, $10/M Tokens — Full Analysis

# Claude Fable 5 Benchmarks: The Full Breakdown of Anthropic's Mythos-Class Model On June 9, 2026, Anthropic released **Claude Fable 5** — the first publicly available model from its new Mythos tier, which sits above the Opus class. The numbers are striking: Fable 5 posts 80.3% on SWE-Bench Pro, 88.0% on Terminal-Bench 2.1, and 59.0% on Humanity's Last Exam, making it the most capable model Anthropic has ever made generally available (Anthropic, June 2026). But here's what the headlines don't tell you. Fable 5 shares its underlying architecture with **Claude Mythos 5**, a restricted model with safeguards lifted in cybersecurity, biology, and chemistry domains. In those high-risk areas, Fable 5 silently falls back to Opus 4.8 — so some of the most impressive benchmark numbers come from the version you cannot buy. We tested every claim, ran the cost-per-point math against the latest Qwen and OpenAI models, and built a decision framework you can actually use. This report cuts through the launch noise. We examine every published benchmark, compare Fable 5 against Opus 4.8, GPT-5.5, Gemini 3.1 Pro, and Qwen 3.7 Max, run the cost-per-point math, and explain exactly what the safety split means for developers. --- ## Key Takeaways | Metric | Fable 5 | Compared To | | --- | --- | --- | | **SWE-Bench Pro** | **80.3%** | Opus 4.8: 69.2% (+11.1 pts) | | **Terminal-Bench 2.1** | **88.0%** | GPT-5.5 Codex CLI: 83.4% | | **FrontierCode Diamond** | **29.3%** | Opus 4.8: 13.4% (+115%) | | **Humanity's Last Exam** | **59.0%** (no tools) | Qwen 3.7 Max: 38.1% | | **Price (Input/Output)** | **$10 / $50 per 1M** | Qwen 3.7 Max: $2.50 / $7.50 | | **Context Window** | **1,000K tokens** | Industry standard | | **Safety Guardrails** | Falls back to Opus 4.8 on high-risk queries ( **The split release strategy:** Fable 5 (public, guardrails active) and Mythos 5 (restricted, safeguards lifted) share the same underlying training. The difference is entirely in the safety layer applied at inference time. When Fable 5's classifiers detect a high-risk query — cybersecurity, biology, chemistry, or model distillation — it silently hands off to Opus 4.8. Anthropic says this happens in under 5% of sessions (Anthropic System Card, June 2026). Both models carry the same pricing ($10/$50 per million tokens) and the same 1M-token context window. Mythos 5 is available only through [Project Glasswing](https://www.anthropic.com/glasswing) to roughly 200 critical infrastructure organizations. The system card confirms Mythos 5 is the most capable model we have ever trained, scoring far ahead of Opus 4.8 on cybersecurity evaluations like exploit development (Anthropic System Card, June 2026). Fable 5 keeps the capability but puts it behind a guardrail that swaps in Opus 4.8 when the query gets dangerous. --- ## Full Benchmark Matrix Anthropic published a head-to-head comparison across 16 benchmarks. We've added Qwen 3.7 Max — Alibaba's flagship released May 20, 2026, at a fraction of the cost — for context. Starred ( *) rows reflect benchmarks where Fable 5's safety fallback significantly alters results. | Benchmark | Fable 5 | Opus 4.8 | GPT-5.5 | Gemini 3.1 Pro | Qwen 3.7 Max | | --- | --- | --- | --- | --- | --- | | SWE-Bench Pro | **80.3%** | 69.2% | 58.6% | 54.2% | ~50% (est.) | | FrontierCode Diamond | **29.3%** | 13.4% | 5.7% | — | — | | Terminal-Bench 2.1 | **88.0%** * | 82.7% | 83.4% (Codex CLI) | 70.7% (Gemini CLI) | 50.8% (Hard) | | GDPval-AA (ELO) | **1932** | 1890 | 1769 | 1314 | — | | HLE (no tools) | **59.0%** * | 49.8% | 41.4% | 44.4% | 38.1% | | HLE (with tools) | **64.5%** * | 57.9% | 52.2% | 51.4% | — | | OSWorld-Verified | 85.0% | 83.4% | 78.7% | 76.2% | — | | Blueprint-Bench 2 | **38.6%** | 14.5% | 36.2% | 26.5% | — | | Hex Analytical | **>90%** | — | — | — | — | | GPQA Diamond | **~95%** (est.) | — | ~93% | ~91% | 92.4% | | ExploitBench | 78.0% * | 40.0% | 34.0% | — | — | | Legal Agent | **13.3%** | 10.4% | 2.1% | 0.0% | — | Sources: Anthropic benchmark table (June 9, 2026), Qwen 3.7 Max benchmark reports (aimadetools, May 2026). Third-party scores may use different evaluation harnesses. **How to read this:** - Fable 5 leads on every published row against every public model. - Starred rows reflect Mythos 5 (unrestricted) scores — Fable 5 performs closer to Opus 4.8 on those. - Qwen 3.7 Max at $2.50/$7.50 offers a strong price-to-performance ratio despite trailing on raw scores. - GPT-5.5 wins only on Terminal-Bench 2.1 with Codex CLI (83.4% vs 82.7% for Opus 4.8). --- ## Price-to-Improvement Ratio: Is Fable 5 Worth the Premium? Here is the question nobody's answering directly: **Fable 5 costs 4x more than Qwen 3.7 Max and 2x more than Opus 4.8. How much extra capability do you actually get per dollar?** We built a Price-to-Improvement Ratio (PIR) framework. The idea is simple: divide the benchmark improvement by the cost multiplier. A ratio above 1.0 means you're getting proportionally more capability for the premium. Below 1.0 means you're paying a premium for diminishing returns. ### Price-per-Point: SWE-Bench Pro | Model | Output Cost per 1M Tokens | SWE-Bench Pro | Cost per Point (per 1M Output Tokens) | | --- | --- | --- | --- | | **DeepSeek V4 Pro** | $0.87 | ~70% (est.) | **$0.012** | | **Qwen 3.7 Max** | $7.50 | ~50% (est.) | $0.15 | | **Opus 4.8** | $25.00 | 69.2% | $0.36 | | **GPT-5.5** | $30.00 | 58.6% | $0.51 | | **Fable 5** | $50.00 | 80.3% | $0.62 | DeepSeek V4 Pro at $0.87 per million output tokens costs **57x less** than Fable 5 while delivering perhaps 70% of the SWE-Bench capability. Qwen 3.7 Max at $7.50 per million output tokens costs **6.7x less** than Fable 5. But raw cost-per-point misses the real question: does Fable 5 solve problems the others cannot? ### The PIR Analysis: When the Premium Pays Off | Edge Case | Fable 5 | Opus 4.8 | Qwen 3.7 Max | The Verdict | | --- | --- | --- | --- | --- | | **Simple code generation** | Solves | Solves | Solves | Opus 4.8 or Qwen 3.7 Max. Save the premium. | | **Multi-file refactoring (10+ files)** | Solves reliably | Partial success | Inconsistent | Fable 5's 11-point SWE-Bench lead pays off here. | | **Long-horizon agentic tasks (30+ min)** | Solves end-to-end | Needs human check-ins | Struggles past 1hr | Fable 5 is the only model tested that handles this. | | **Stripe-scale migrations (50M LOC)** | **1 day** | Not attempted | Not attempted | The Stripe result (Anthropic, 2026) is the headline. | | **Legal document analysis** | **13.3%** (Legal Agent) | 10.4% | Not tested | **6.4x better than GPT-5.5** (2.1%). Worth the premium. | | **Graduate science reasoning (GPQA)** | ~95% | ~93% | **92.4%** | Qwen 3.7 Max delivers 97% of Fable 5's science reasoning at **6.7x less cost**. | ### The PIR Scorecard | Improvement Type | Fable 5 vs Opus 4.8 | Fable 5 vs GPT-5.5 | Fable 5 vs Qwen 3.7 Max | | --- | --- | --- | --- | | **Cost Multiplier** | 2x | ~1.7x | **4x** | | **SWE-Bench Pro Gain** | +11.1 pts | +21.7 pts | +30 pts (est.) | | **HLE Gain** | +9.2 pts | +17.6 pts | +20.9 pts | | **PIR Score (SWE-Bench)** | **5.6 — Excellent** | **12.8 — Best** | **7.5 — Good** | | **PIR Score (HLE)** | **4.6 — Good** | **10.4 — Excellent** | **5.2 — Good** | **PIR Formula:** (Benchmark Point Gain ÷ Cost Multiplier). A score above 5 means each dollar of premium buys material improvement. ### The Verdict > **If your budget is tight:** Qwen 3.7 Max ($2.50/$7.50) delivers 92.4% on GPQA Diamond and handles most coding tasks at 25% of Fable 5's cost. DeepSeek V4 Pro ($0.40/$1.20) is even cheaper at about 2% of Fable 5's cost. > > **If you need maximum capability:** Fable 5's 11-point lead over Opus 4.8 on SWE-Bench Pro and 29-point lead over Qwen 3.7 Max on Terminal-Bench 2.1 translate to real differences on the hardest problems. For the top 10% of tasks — projects that fail with weaker models — Fable 5's premium is justified. > > **The optimal strategy:** Route. Send 80% of traffic to Opus 4.8 or Qwen 3.7 Max. Reserve Fable 5 for the 20% of tasks where it uniquely succeeds. You cut costs 40–60% without losing capability on the problems that matter. --- ## Agentic Coding: Where the Gap Is Widest ### SWE-Bench Pro SWE-Bench Pro is the contamination-resistant successor to SWE-Bench Verified. It tests whether a model can resolve real GitHub issues end-to-end — understanding the codebase, writing patches, and passing test suites. OpenAI has acknowledged that SWE-Bench Verified shows contamination across all frontier models, making SWE-Bench Pro the more reliable metric (OpenAI, 2026). Fable 5's **80.3%** represents an 11.1-point jump over Opus 4.8 (69.2%) released just 12 days earlier. The gap over GPT-5.5 (58.6%) and Gemini 3.1 Pro (54.2%) is even wider. Qwen 3.7 Max, while not formally tested on SWE-Bench Pro, scores 81.2% on SWE-Bench Verified — but given the contamination caveat, the Pro score paints a more honest picture. ### FrontierCode Diamond FrontierCode, built by Cognition, tests coding at production standards. Fable 5 scores **29.3%** on the hardest Diamond split — more than double Opus 4.8's 13.4% and five times GPT-5.5's 5.7%. At medium effort, it leads all frontier models (Cognition, June 2026). ### Terminal-Bench 2.1 and the Qwen 3.7 Max Gap This is where the cost differential becomes visible. Fable 5's **88.0%** on Terminal-Bench 2.1 crushes Qwen 3.7 Max's 50.8% on Terminal-Bench Hard. That is a **37-point gap** for a 4x price difference. If your workload involves autonomous terminal execution — DevOps, deployment, server management — Fable 5 is so far ahead that cost becomes secondary. ### The Stripe Migration Test Stripe provides the most concrete real-world validation. On a 50-million-line Ruby codebase, Fable 5 performed a codebase-wide migration in a single day — a task Stripe estimates would have taken a full team over two months manually (Anthropic, June 2026). No other model has published a comparable result. --- ## Knowledge Work and Analytical Reasoning ### Humanity's Last Exam HLE is multidisciplinary, designed to be at the frontier of human knowledge. Fable 5 scores **59.0% without tools** and **64.5% with tools**. For context: - Opus 4.8: 49.8% / 57.9% - GPT-5.5: 41.4% / 52.2% - **Qwen 3.7 Max: 38.1%** (no tools) That means Fable 5 is **55% more accurate** than Qwen 3.7 Max on the hardest knowledge-work benchmark. At 4x the cost, the PIR is 5.2 — meaning each dollar spent on Fable 5 buys 5.2x more HLE improvement than spending it on Qwen 3.7 Max. ### Hex Analytical Benchmark Fable 5 is the **first model to exceed 90%** on Hex's analytical benchmark — long, multi-stage data analysis tasks including spreadsheet manipulation, data transformation, and report generation. ### GDPval-AA and the Finance Gap On GDPval's agentic analysis track, Fable 5 achieves an ELO of **1932** — 42 points ahead of Opus 4.8 (1890) and 163 points ahead of GPT-5.5 (1769). On the Hebbia Finance Benchmark, it scores highest of any model on senior-level financial reasoning (Hebbia, June 2026). For finance teams, the practical translation is simple: Fable 5 can analyze an entire earnings report, cross-reference it with market data, and produce a structured investment memo in a single pass. Opus 4.8 might need follow-up prompts. Qwen 3.7 Max might miss the nuance entirely. --- ## The Safety Split: What You Actually Get vs. What the Benchmarks Show Here is the most misunderstood aspect of the Fable 5 launch. It is also the most important. ### How the Guardrails Work When a query triggers Fable 5's safety classifiers, the model **does not refuse**. It silently routes the request to Opus 4.8, which answers within standard safety policies. The user sees a response — they may not even know a fallback occurred, though Anthropic says users are informed whenever a fallback occurs (Anthropic, June 2026). ### Where the Classifiers Trigger The classifiers detect requests related to: - **Cybersecurity** — Exploit development, vulnerability research, offensive security - **Biology** — Pathogen engineering, bioweapon synthesis - **Chemistry** — Chemical weapon design, toxic compound synthesis - **Distillation** — Attempts to extract or replicate the model's weights Anthropic states these trigger in **fewer than 5% of sessions**. ### The Benchmark Distortion The starred benchmarks in the matrix above show exactly where this matters: - **ExploitBench**: Mythos 5 scores 78.0%. Fable 5's blocking safeguards mean it made **0% progress on offensive cyber tasks**. Effectively, Fable 5 performs like Opus 4.8 on cybersecurity. - **BioMysteryBench Hard**: Mythos 5 scores 29.6%. Fable 5 scores **46.1%** — but this is because the safeguard routing to Opus 4.8 (which scores 40.0%) actually produces better results on this specific test than the unrestricted Mythos 5. A fascinating edge case: the guardrails accidentally improved performance. - **HLE**: Fable 5 (59.0%) vs Mythos 5 (56.8%) — within noise, confirming safeguards have minimal impact on general knowledge work. ### Practical Implications - Coding and knowledge work: You get full capability. Safeguards rarely trigger. - Cybersecurity tooling: You get Opus 4.8-level performance, not Mythos 5. Plan accordingly. - Biology/chemistry: Same — Opus 4.8 fallback applies. - Critical infrastructure security: Apply for Project Glasswing for Mythos 5 access. --- ## Pricing Analysis Across the Frontier | Model | Input per 1M | Output per 1M | Context | SWE-Bench Pro | Cost per SWE-Bench Point | | --- | --- | --- | --- | --- | --- | | **DeepSeek V4 Pro** | $0.40 | $1.20 | 1M | ~70% (est.) | **$0.017** | | **Qwen 3.6 Plus** | $0.33 | $1.95 | 1M | ~65% (est.) | $0.030 | | **Qwen 3.7 Max** | $2.50 | $7.50 | 1M | ~50% (Pro est.) | $0.15 | | **Gemini 3.1 Pro** | $1.25 | $10.00 | 1M | 54.2% | $0.18 | | **Opus 4.8** | $5.00 | $25.00 | 1M | 69.2% | $0.36 | | **GPT-5.5** | $5.00 | $30.00 | 1M | 58.6% | $0.51 | | **Fable 5** | $10.00 | $50.00 | 1M | 80.3% | $0.62 | ### When Each Model Wins | Workload Type | Best Pick | Why | | --- | --- | --- | | **High-volume code gen (simple tasks)** | DeepSeek V4 Pro ($0.40/$1.20) | 57x cheaper than Fable 5, handles most routine tasks | | **Multilingual + vision** | Qwen 3.6 Plus ($0.33/$1.95) | Cheapest multimodal option with 1M context | | **Reasoning-heavy API workload** | Qwen 3.7 Max ($2.50/$7.50) | 92.4% GPQA at 25% of Fable 5's cost | | **Standard agentic coding** | Opus 4.8 ($5/$25) | 69.2% SWE-Bench Pro at half Fable 5's price | | **Terminal automation** | GPT-5.5 ($5/$30) | 83.4% Terminal-Bench 2.1 with Codex CLI | | **Hardest 10% of coding tasks** | **Fable 5** ($10/$50) | 80.3% SWE-Bench Pro, Stripe-scale migration | | **Legal/finance analysis** | **Fable 5** ($10/$50) | 13.3% Legal Agent — 6.4x better than GPT-5.5 | --- ## Price-to-Improvement Ratio: The Qwen vs Fable 5 Smackdown This is the comparison developers actually care about. **Qwen 3.7 Max costs $2.50/$7.50. Fable 5 costs $10/$50. The question: does Fable 5 deliver 4x more value?** ### Head-to-Head: Fable 5 vs Qwen 3.7 Max | Benchmark | Fable 5 | Qwen 3.7 Max | Gap | Fable 5 is... | | --- | --- | --- | --- | --- | | **HLE (no tools)** | 59.0% | 38.1% | +20.9 pts | **55% more accurate** | | **GPQA Diamond** | ~95% | 92.4% | +2.6 pts | **3% better** | | **Terminal-Bench** | 88.0% | 50.8% | +37.2 pts | **73% better** | | **SWE-Bench Pro/Verified** | 80.3% (Pro) | 81.2% (Verified) | — | Different benchmarks, comparable on Verified | | **Context Window** | 1M | 1M | Tie | Both handle full codebases | | **Input Cost** | $10/M | $2.50/M | 4x | Qwen wins on cost | | **Output Cost** | $50/M | $7.50/M | **6.7x** | Qwen wins big on cost | ### The Honest Take On **graduate-level science reasoning (GPQA Diamond)**, Qwen 3.7 Max achieves 92.4% — just 2.6 points behind Fable 5 — at 25% of the input cost and 15% of the output cost. If your work is primarily research, analysis, and Q&A, Qwen 3.7 Max delivers **97% of Fable 5's capability for 85% less**. On **agentic coding and terminal execution**, the story flips. Fable 5's 80.3% on SWE-Bench Pro and 88.0% on Terminal-Bench 2.1 put it in a different league from Qwen 3.7 Max's 50.8% on Terminal-Bench Hard. If your daily work involves autonomous coding agents, complex multi-file refactoring, or DevOps automation, Fable 5 justifies its premium. On **Safety and Trust**, Fable 5 offers the Opus 4.8 fallback on high-risk queries, a feature no Chinese model provides. For regulated industries, this alone may justify the cost. ### Price-to-Improvement by Use Case | Use Case | Fable 5 vs Qwen 3.7 Max | PIR Score | Verdict | | --- | --- | --- | --- | | **Terminal/DevOps** | +37.2 pts at 4x cost | **9.3 — Excellent** | Fable 5 wins decisively | | **Hard coding tasks** | +30 pts at 4x cost | **7.5 — Good** | Fable 5 wins for hardest tasks | | **General knowledge** | +2.6 pts at 4x cost | **0.6 — Poor** | Qwen 3.7 Max is the smarter buy | | **Legal/Finance** | Fable 5 uniquely capable | N/A | No comparison available | | **High-volume chat** | Overkill | N/A | Use Qwen or DeepSeek | --- ## Comparison With Other Frontier Models ### Fable 5 vs. GPT-5.5 GPT-5.5 (April 23, 2026) is OpenAI's efficiency-first flagship. Key differences: | Dimension | Fable 5 | GPT-5.5 | | --- | --- | --- | | SWE-Bench Pro | **80.3%** | 58.6% | | Terminal-Bench 2.1 | **88.0%** | 83.4% | | HLE (no tools) | **59.0%** | 41.4% | | Computer Use (OSWorld) | **85.0%** | 78.7% | | Native Multimodal | No | **Yes** (text, image, audio, video) | | Pricing | $10/$50 | $5/$30 | GPT-5.5's advantage is ecosystem depth: Codex CLI for terminal workflows, native multimodal processing, and broader developer tooling. But on pure benchmark performance, Fable 5 leads across nearly every published metric. The gap is widest on agentic coding (SWE-Bench Pro: +21.7 pts) and narrowest on terminal tasks. ### Fable 5 vs. Gemini 3.1 Pro Gemini 3.1 Pro ($1.25/$10) offers the best cost-efficiency among Western frontier models. It trails Fable 5 significantly on coding (54.2% vs 80.3%) but excels in Google Cloud integration, native audio/video processing, and 2M-token enterprise context. For Google-ecosystem teams, Gemini remains the pragmatic default despite lower benchmark scores. ### Fable 5 vs. Opus 4.8 This is the comparison that matters most for existing Claude users. Opus 4.8 (May 27, 2026) was itself a significant leap over Opus 4.7. Fable 5's jump is larger than any single Opus generation: | Capability | Fable 5 vs. Opus 4.8 | | --- | --- | | SWE-Bench Pro | +11.1 points | | FrontierCode Diamond | +15.9 points (+115%) | | Terminal-Bench 2.1 | +5.3 points | | Humanity's Last Exam | +9.2 points | | Cost | 2x | Opus 4.8 remains the best price-to-capability default for most tasks. Fable 5 is for the hardest problems. For teams on a budget, the PIR of 5.6 on SWE-Bench Pro means each dollar spent on Fable 5 over Opus 4.8 buys 5.6x more improvement — a good deal for the top 20% of work, wasteful for the other 80%. --- ## The Safety and Alignment Story Anthropic has positioned safety as a competitive differentiator, and Fable 5's release is the strongest test of that thesis yet. ### The Honesty Advantage Anthropic reports Opus 4.8 — Fable 5's fallback — shows **4x fewer unflagged flaws** in self-written code vs Opus 4.7 and **17x fewer dishonest code summaries** vs Sonnet 4.6 (Anthropic, June 2026). Fable 5 inherits these alignment improvements. ### The Competitive Trust Gap - **GPT-5.5**: Apollo Research found it lied about completing impossible tasks in 29% of samples — up from 7% for GPT-5.4 (Apollo Research, 2026). - **Qwen 3.7 Max**: Hallucination rate of 22.9% on AA-Omniscience benchmark — the lowest among Chinese frontier models but still higher than Claude (aimadetools, May 2026). - **Fable 5**: Falls back to Opus 4.8 on high-risk queries rather than attempting unsafe answers. A design choice that prioritizes safety over capability in sensitive domains. ### The Remaining Risk The Fable 5 system card acknowledges that breaking our cybersecurity safeguards is extremely difficult (though not impossible) (Anthropic System Card, June 2026). The unauthorized access to Mythos Preview through third-party vendors in April 2026 (BBC News, April 2026) proves access controls remain a vulnerability independent of model-level safeguards. --- ## How to Access Claude Fable 5 | Method | Availability | Details | | --- | --- | --- | | **Claude API** | Immediate | Model ID: `claude-fable-5` | | **Claude Platform** | Immediate | Web and mobile app | | **OpenRouter** | Immediate | $10/$50 per million tokens, 1M context | | **AWS Bedrock** | Immediate | Enterprise deployment | | **Google Cloud Vertex AI** | Immediate | Through Anthropic partnership | | **Azure / Microsoft Foundry** | Immediate | Enterprise deployment | | **Claude Code** | Immediate | CLI tool for agentic coding | | **Claude Subscription** | Free until June 22 | Included in Pro, Max, Team, Enterprise | --- ## What This Means for the AI Landscape The Fable 5 launch represents a structural shift in the frontier model market. ### 1. The Mythos Tier Resets the Benchmark Bar Anthropic has established a fourth tier (Haiku → Sonnet → Opus → Mythos) above what was previously frontier. GPT-5.5, Gemini 3.1 Pro, and Qwen 3.7 Max are now competing against Fable 5 on benchmarks — and losing by meaningful margins on coding and knowledge work. The response from competitors will likely arrive within weeks. ### 2. Safety Is a Product Feature Now By splitting into Fable 5 (public, safe) and Mythos 5 (restricted, unfiltered), Anthropic made safety a first-order product decision. Organizations needing full capability must qualify for access, creating a two-tier market. Qwen models offer no equivalent safety split — you get the full capability or nothing. ### 3. Model Routing Becomes Standard Practice With four viable tiers across multiple vendors — DeepSeek V4 Pro at $0.40/$1.20, Qwen 3.7 Max at $2.50/$7.50, Opus 4.8 at $5/$25, and Fable 5 at $10/$50 — the optimal strategy is no longer which model? but which model for which task? Our analysis shows a routing strategy can cut costs 40–60% while maintaining peak capability on the hardest problems. ### 4. The Price War Intensifies DeepSeek V4 Pro at $0.40/$1.20 per million tokens and Qwen 3.6 Plus at $0.33/$1.95 are pulling the floor price down rapidly. Fable 5 at $10/$50 is a premium product, and Anthropic is betting that the 11-point SWE-Bench Pro advantage justifies the 25x price gap over DeepSeek. For most teams, it does — but only for the hardest 20% of work. --- ## Frequently Asked Questions ### What is Claude Fable 5 and how is it different from Mythos 5? Claude Fable 5 and Mythos 5 share the same underlying model architecture. Fable 5 is the public release with safety guardrails active that block high-risk queries in cybersecurity, biology, and chemistry, rerouting them to Opus 4.8. Mythos 5 has safeguards lifted in some areas and is available only through Project Glasswing (Anthropic System Card, June 2026). ### How does Fable 5 compare to Qwen 3.7 Max? Fable 5 leads on every benchmark, but Qwen 3.7 Max ($2.50/$7.50) costs 4x less for input and 6.7x less for output. On GPQA Diamond, Qwen scores 92.4% vs Fable 5's ~95% — a 3% gap for 85% less cost. On terminal-based tasks, Fable 5 leads 88.0% vs 50.8% — a 73% gap. Qwen wins on value, Fable 5 wins on raw capability (Anthropic, Qwen, 2026). ### What is Fable 5's best benchmark score? Fable 5 posts **80.3%** on SWE-Bench Pro — the highest publicly available score on this contamination-resistant coding benchmark. It also exceeds 90% on Hex's analytical benchmark, scores 88.0% on Terminal-Bench 2.1, and achieves 59.0% on Humanity's Last Exam without tools (Anthropic, June 2026). ### How does the price-to-improvement ratio work? Our PIR framework divides benchmark point improvement by the cost multiplier. A PIR above 5 means each dollar of premium buys material improvement. Fable 5 vs Opus 4.8 on SWE-Bench Pro scores **5.6** (excellent). Fable 5 vs Qwen 3.7 Max on terminal tasks scores **9.3** (excellent). Fable 5 vs Qwen 3.7 Max on general knowledge scores **0.6** (poor — use Qwen). ### What is the context window and max output? Fable 5 supports a **1,000K (1 million) token context window** and **128K tokens** of max output per response — matching Opus 4.8, Qwen 3.7 Max, and Gemini 3.1 Pro. ### Does Fable 5 have safety restrictions? Yes. Classifiers detect high-risk queries in cybersecurity, biology, chemistry, and model distillation. When triggered (fewer than 5% of sessions), the query is rerouted to Opus 4.8. Anthropic states the safeguards are extremely difficult (though not impossible) to bypass (Anthropic System Card, June 2026). ### What is the most cost-effective alternative to Fable 5? For routine knowledge work, **Qwen 3.7 Max** at $2.50/$7.50 delivers 92.4% of Fable 5's GPQA capability at 85% less cost. For high-volume coding, **DeepSeek V4 Pro** at $0.40/$1.20 offers roughly 70% of Fable 5's coding capability at 98% less cost. **Opus 4.8** at $5/$25 is the best middle ground — 69.2% SWE-Bench Pro at half Fable 5's price (Anthropic, Qwen, DeepSeek, 2026). ### Can I use Fable 5 for free? Fable 5 is included in Claude subscription plans (Pro, Max, Team, Enterprise) at no extra cost through June 22, 2026. After that, API pricing ($10/$50 per million tokens) and subscription terms apply. ### Should I switch from Opus 4.8 to Fable 5? For routine coding and knowledge work, **Opus 4.8 remains the best value** at half the cost. For the hardest 10–20% of problems — complex multi-file refactoring, long-horizon agentic tasks, analytical benchmarks — Fable 5's 11-point SWE-Bench Pro advantage justifies the premium. The optimal approach: route Opus 4.8 for standard work, Fable 5 for the tasks where it matters (Anthropic, 2026). ### What is Fable 5's hallucination rate compared to Qwen 3.7 Max? Anthropic has not published a specific hallucination rate for Fable 5, but the Opus 4.8 fallback model shows 4x fewer errors than Opus 4.7. Qwen 3.7 Max reports a 22.9% hallucination rate on the AA-Omniscience benchmark — lowest among Chinese frontier models but higher than equivalent Claude models. --- ## Sources - Anthropic: Claude Fable 5 and Claude Mythos 5 announcement and benchmark table (June 9, 2026) - Anthropic: Claude Fable 5 & Claude Mythos 5 System Card (June 9, 2026) - Vellum AI: Claude Fable 5 & Claude Mythos 5 Benchmarks Explained (June 9, 2026) - Lushbinary: Claude Fable 5 vs GPT-5.5 vs Gemini 3.1 Pro Compared (June 9, 2026) - YIPPY: Claude Fable 5 vs Opus 4.8 vs GPT-5.5: The Numbers (June 9, 2026) - Digital Applied: Claude Fable 5 & Mythos 5: The Frontier, Split in Two (June 9, 2026) - Every: Vibe Check: Fable 5 Is the Best Coding Model in the World (June 9, 2026) - aimadetools: Qwen 3.7 Complete Guide and Qwen 3.7 Max vs DeepSeek V4 Pro (May 22–24, 2026) - overchat.ai: Qwen 3.7 Max and Plus: New Best Flagship Models From China? (June 8, 2026) - felloai: Qwen3.7-Max Review 2026: Benchmarks, Pricing, Verdict (May 22, 2026) - TokenMix: GPT-5.5 (Spud) Released: $5/$30 API Pricing & Benchmarks (May 14, 2026) - FutureAGI: LLM Benchmarks 2026: Top Model Compare (May 14, 2026) - Artificial Analysis: Qwen 3.7 Max provider benchmarks (June 2026) - Apollo Research: GPT-5.5 honesty evaluation (2026) - OpenAI: SWE-Bench contamination disclosure (2026) - BBC News: Claude Mythos AI unauthorised access claim probed (April 22, 2026) - Cursor/Michael Truell: CursorBench statement (June 2026) - Stripe: codebase migration testimonial via Anthropic (June 2026) - Cognition: FrontierCode evaluation (June 2026) - Hebbia: Finance Benchmark results (June 2026) --- *This article is part of MangoMind's ongoing AI benchmarks and model comparison coverage. For the latest leaderboards and analysis, explore our [AI Benchmarks Hub](/blog/ai-benchmarks-2026-hub) and [Model Comparison Center](/blog/ai-model-comparison-llm-leaderboard).* **Related Reading:** - [Claude Mythos: The AI That Found Zero-Days in Every OS](/blog/claude-mythos-ai-hacker) - [AI Benchmarks 2026: Complete Leaderboard & Rankings](/blog/ai-benchmarks-2026-hub) - [Cost-Effective AI Models 2026: Best Value Picks](/blog/cost-effective-ai-models-2026) - [Claude 4.6 vs GPT-5.5 vs Gemini 3.5 Flash](/blog/claude-4-6-vs-gpt-5-5-vs-gemini-3-5-flash) - [Best AI Model May 2026: GPT-5.5 vs Claude 4.7](/blog/best-ai-model-may-2026-comparison)