DeepSeek V4.1 Flash 1017 vs Claude Opus 5.5
DeepSeek V4.1 Flash 1017 comes out ahead, 79 to 69 on our weighted score, and it is the cheaper option too.
- Our pick
DeepSeekDeepSeek V4.1 Flash 1017
79/100- ECI158.8
- Price$0.15 / $0.60
- Context1M
AnthropicClaude Opus 5.5
69/100- ECI168.4
- Price$4.00 / $20.00
- 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 Opus 5.5 (69). It leads on price. Claude Opus 5.5 wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityClaude Opus 5.5Capabilities Index (ECI): Claude Opus 5.5 168.4 · DeepSeek V4.1 Flash 1017 158.8
- Lowest priceDeepSeek V4.1 Flash 1017DeepSeek V4.1 Flash 1017 $0.263 · Claude Opus 5.5 $8.00 per 1M tokens (3:1 blend)
- Longest contextAbout the sameDeepSeek V4.1 Flash 1017 1,000,000 · Claude Opus 5.5 1,000,000 tokens
- Widest inputsClaude Opus 5.5DeepSeek V4.1 Flash 1017: Text, Images · Claude Opus 5.5: Text, Images, PDFs
- Self-hostingDeepSeek V4.1 Flash 1017Publishes downloadable weights (MIT)
| Measure | Weight | DeepSeek V4.1 Flash 1017 | Claude Opus 5.5 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 87 | 99 |
| Price | 25% | 74 | 7 |
| Inputs & features | 15% | 70 | 80 |
| Context window | 10% | 60 | 60 |
| Overall | 100% | 79/100 | 69/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek V4.1 Flash 1017DeepSeek | Claude Opus 5.5Anthropic |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 158.8 | 168.4 (best) |
| ECI rank | #19 of 165 | #2 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 93.2% (best) | 90.6% |
| FrontierMath Tiers 1–3Research-level mathematics | 71.2% | 91.2% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 99.4% | 100% (best) |
| SimpleQA VerifiedShort factual questions | 42.5% | 72.2% (best) |
| Price per million tokens | ||
| Input | $0.15 (best) | $4.00 |
| Output | $0.60 (best) | $20.00 |
| Cached input | $0.003 (best) | $0.20 |
| Blended (3:1) | $0.263 (best) | $8.00 |
| Long-context rate | Same rate | Same rate |
| Price source | Official DeepSeek API | Official Anthropic API |
| Limits | ||
| Context window | 1,000,000 tokens | 1,000,000 tokens |
| Max output | 384,000 tokens (best) | 128,000 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yeslow · high · max | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes |
| Structured output | Yes | Yes |
| Availability | ||
| Weights | OpenMIT | Proprietary |
| API model ID | deepseek-flash | claude-opus-5-5 |
| API providers | 40 (best) | 36 |
| Released | Oct 17, 2026 | Sep 22, 2026 |
| Knowledge cutoff | May 2025 | Jun 2026 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek V4.1 Flash 1017$2.70
- Claude Opus 5.5$80.00
Which should you choose?
Which is better: DeepSeek V4.1 Flash 1017 or Claude Opus 5.5?
DeepSeek V4.1 Flash 1017 is the better all-round choice, scoring 79/100 against Claude Opus 5.5 (69). It leads on price. Claude Opus 5.5 wins on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek V4.1 Flash 1017 or Claude Opus 5.5?
DeepSeek V4.1 Flash 1017 is cheaper at $0.15 input / $0.60 output per million tokens (official DeepSeek API price). Claude Opus 5.5 costs $4.00 input / $20.00 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 $8.00 for Claude Opus 5.5 (30× as much).
Which scores higher on benchmarks?
Claude Opus 5.5 scores higher on the Capabilities Index (ECI): Claude Opus 5.5 168.4 (#2 of 165) and DeepSeek V4.1 Flash 1017 158.8 (#19 of 165). Their confidence ranges do not overlap (165.4–173.0 vs 156.7–162.2), so the gap is a real one. On individual benchmarks: GPQA Diamond — DeepSeek V4.1 Flash 1017 93.2%, Claude Opus 5.5 90.6%; FrontierMath Tiers 1–3 — Claude Opus 5.5 91.2%, DeepSeek V4.1 Flash 1017 71.2%; OTIS Mock AIME 2024–2025 — Claude Opus 5.5 100%, DeepSeek V4.1 Flash 1017 99.4%; SimpleQA Verified — Claude Opus 5.5 72.2%, DeepSeek V4.1 Flash 1017 42.5%.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4.1 Flash 1017 and Claude Opus 5.5 yet, so there is no like-for-like coding score. On overall capability, Claude Opus 5.5 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?
DeepSeek V4.1 Flash 1017 and Claude Opus 5.5 share the same 1,000,000-token context window. Maximum output per response: DeepSeek V4.1 Flash 1017 up to 384,000, Claude Opus 5.5 up to 128,000 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4.1 Flash 1017 accepts text and images; Claude Opus 5.5 accepts text, images and PDFs. Claude Opus 5.5 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 Opus 5.5 is proprietary.
Which is newer?
DeepSeek V4.1 Flash 1017 is the newest, released Oct 17, 2026. Claude Opus 5.5 came out Sep 22, 2026. Knowledge cutoff: DeepSeek V4.1 Flash 1017 May 2025, Claude Opus 5.5 Jun 2026.
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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