Claude Fable 5.1 vs DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 comes out ahead, 79 to 66 on our weighted score, and it is the cheaper option too.
AnthropicClaude Fable 5.1
66/100- ECI166.4
- Price$10.00 / $50.00
- Context1M
- Our pick
DeepSeekDeepSeek V4.1 Flash 1017
79/100- ECI158.8
- Price$0.15 / $0.60
- Context1M
Add a model
Make it a three-way comparison.
DeepSeek V4.1 Flash 1017 is our pick
DeepSeek V4.1 Flash 1017 is the better all-round choice, scoring 79/100 against Claude Fable 5.1 (66). It leads on price. Claude Fable 5.1 wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityClaude Fable 5.1Capabilities Index (ECI): Claude Fable 5.1 166.4 · DeepSeek V4.1 Flash 1017 158.8
- Lowest priceDeepSeek V4.1 Flash 1017DeepSeek V4.1 Flash 1017 $0.263 · Claude Fable 5.1 $20.00 per 1M tokens (3:1 blend)
- Longest contextAbout the sameClaude Fable 5.1 1,000,000 · DeepSeek V4.1 Flash 1017 1,000,000 tokens
- Widest inputsClaude Fable 5.1Claude Fable 5.1: Text, Images, PDFs · DeepSeek V4.1 Flash 1017: Text, Images
- Self-hostingDeepSeek V4.1 Flash 1017Publishes downloadable weights (MIT)
| Measure | Weight | Claude Fable 5.1 | DeepSeek V4.1 Flash 1017 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 97 | 87 |
| Price | 25% | 0 | 74 |
| Inputs & features | 15% | 80 | 70 |
| Context window | 10% | 60 | 60 |
| Overall | 100% | 66/100 | 79/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Claude Fable 5.1Anthropic | DeepSeek V4.1 Flash 1017DeepSeek |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 166.4 (best) | 158.8 |
| ECI rank | #6 of 165 (best) | #19 of 165 |
| GPQA DiamondGraduate-level science questions | — | 93.2% |
| FrontierMath Tiers 1–3Research-level mathematics | 90.2% (best) | 71.2% |
| OTIS Mock AIME 2024–2025Competition mathematics | 100% (best) | 99.4% |
| SimpleQA VerifiedShort factual questions | 70.8% (best) | 42.5% |
| Price per million tokens | ||
| Input | $10.00 | $0.15 (best) |
| Output | $50.00 | $0.60 (best) |
| Cached input | $0.25 | $0.003 (best) |
| Blended (3:1) | $20.00 | $0.263 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Anthropic API | Official DeepSeek API |
| Limits | ||
| Context window | 1,000,000 tokens | 1,000,000 tokens |
| Max output | 128,000 tokens | 384,000 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | Yes | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yeslow · medium · high · xhigh · max | Yeslow · high · max |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | Proprietary | OpenMIT |
| API model ID | claude-fable-5-1 | deepseek-flash |
| API providers | 37 | 40 (best) |
| Released | Sep 1, 2026 | Oct 17, 2026 |
| Knowledge cutoff | Jun 2026 | May 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Claude Fable 5.1$200.00
- DeepSeek V4.1 Flash 1017$2.70
Which should you choose?
Which is better: Claude Fable 5.1 or DeepSeek V4.1 Flash 1017?
DeepSeek V4.1 Flash 1017 is the better all-round choice, scoring 79/100 against Claude Fable 5.1 (66). It leads on price. Claude Fable 5.1 wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Claude Fable 5.1 or DeepSeek V4.1 Flash 1017?
DeepSeek V4.1 Flash 1017 is cheaper at $0.15 input / $0.60 output per million tokens (official DeepSeek API price). Claude Fable 5.1 costs $10.00 input / $50.00 output per million tokens (official Anthropic API price). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for DeepSeek V4.1 Flash 1017 versus $20.00 for Claude Fable 5.1 (76× as much).
Which scores higher on benchmarks?
Claude Fable 5.1 scores higher on the Capabilities Index (ECI): Claude Fable 5.1 166.4 (#6 of 165) and DeepSeek V4.1 Flash 1017 158.8 (#19 of 165). Their confidence ranges do not overlap (163.6–170.8 vs 156.7–162.2), so the gap is a real one. On individual benchmarks: FrontierMath Tiers 1–3 — Claude Fable 5.1 90.2%, DeepSeek V4.1 Flash 1017 71.2%; OTIS Mock AIME 2024–2025 — Claude Fable 5.1 100%, DeepSeek V4.1 Flash 1017 99.4%; SimpleQA Verified — Claude Fable 5.1 70.8%, DeepSeek V4.1 Flash 1017 42.5%.
Which is better for coding?
There are no published SWE-bench Verified results for Claude Fable 5.1 and DeepSeek V4.1 Flash 1017 yet, so there is no like-for-like coding score. On overall capability, Claude Fable 5.1 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Claude Fable 5.1 and DeepSeek V4.1 Flash 1017 share the same 1,000,000-token context window. Maximum output per response: Claude Fable 5.1 up to 128,000, DeepSeek V4.1 Flash 1017 up to 384,000 tokens.
Which can read images, PDFs, audio or video?
Claude Fable 5.1 accepts text, images and PDFs; DeepSeek V4.1 Flash 1017 accepts text and images. Claude Fable 5.1 handles the widest range of inputs.
Are any of these open source?
DeepSeek V4.1 Flash 1017 publishes its weights (MIT) and can be self-hosted; Claude Fable 5.1 is proprietary.
Which is newer?
DeepSeek V4.1 Flash 1017 is the newest, released Oct 17, 2026. Claude Fable 5.1 came out Sep 1, 2026. Knowledge cutoff: Claude Fable 5.1 Jun 2026, DeepSeek V4.1 Flash 1017 May 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.
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