DeepSeek V4.1 Flash 1017 vs DeepSeek V4.1 Flash
DeepSeek V4.1 Flash 1017 comes out ahead, 79 to 72 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
- DeepSeek
DeepSeek V4.1 Flash
72/100- ECI156.1
- Price$0.28 / $1.20
- Context1M
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DeepSeek V4.1 Flash 1017 is our pick
DeepSeek V4.1 Flash 1017 is the better all-round choice, scoring 79/100 against DeepSeek V4.1 Flash (72). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityDeepSeek V4.1 Flash 1017Capabilities Index (ECI): DeepSeek V4.1 Flash 1017 158.8 · DeepSeek V4.1 Flash 156.1
- Lowest priceDeepSeek V4.1 Flash 1017DeepSeek V4.1 Flash 1017 $0.263 · DeepSeek V4.1 Flash $0.51 per 1M tokens (3:1 blend)
- Longest contextAbout the sameDeepSeek V4.1 Flash 1017 1,000,000 · DeepSeek V4.1 Flash 1,000,000 tokens
- Widest inputsSame inputsDeepSeek V4.1 Flash 1017: Text, Images · DeepSeek V4.1 Flash: Text, Images
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | DeepSeek V4.1 Flash 1017 | DeepSeek V4.1 Flash |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 87 | 84 |
| Price | 25% | 74 | 61 |
| Inputs & features | 15% | 70 | 60 |
| Context window | 10% | 60 | 60 |
| Overall | 100% | 79/100 | 72/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek V4.1 Flash 1017DeepSeek | DeepSeek V4.1 FlashDeepSeek |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 158.8 (best) | 156.1 |
| ECI rank | #19 of 165 (best) | #34 of 165 |
| GPQA DiamondGraduate-level science questions | 93.2% (best) | 89.8% |
| FrontierMath Tiers 1–3Research-level mathematics | 71.2% (best) | 67.4% |
| OTIS Mock AIME 2024–2025Competition mathematics | 99.4% (best) | 98.3% |
| SimpleQA VerifiedShort factual questions | 42.5% | 42.9% (best) |
| Price per million tokens | ||
| Input | $0.15 (best) | $0.28 |
| Output | $0.60 (best) | $1.20 |
| Cached input | $0.003 | — |
| Blended (3:1) | $0.263 (best) | $0.51 |
| Long-context rate | Same rate | Same rate |
| Price source | Official DeepSeek API | Median of 61 providers |
| Limits | ||
| Context window | 1,000,000 tokens | 1,000,000 tokens |
| Max output | 384,000 tokens | 384,000 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yeslow · high · max | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | OpenMIT | OpenMIT |
| API model ID | deepseek-flash | — |
| API providers | 40 | 64 (best) |
| Released | Oct 17, 2026 | Sep 10, 2026 |
| Knowledge cutoff | May 2025 | 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.
- DeepSeek V4.1 Flash 1017$2.70
- DeepSeek V4.1 Flash$5.20
Which should you choose?
Which is better: DeepSeek V4.1 Flash 1017 or DeepSeek V4.1 Flash?
DeepSeek V4.1 Flash 1017 is the better all-round choice, scoring 79/100 against DeepSeek V4.1 Flash (72). It leads on capability, price 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 DeepSeek V4.1 Flash?
DeepSeek V4.1 Flash 1017 is cheaper at $0.15 input / $0.60 output per million tokens (official DeepSeek API price). DeepSeek V4.1 Flash costs $0.28 input / $1.20 output per million tokens (median across 61 API providers). 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 $0.51 for DeepSeek V4.1 Flash (1.9× as much).
Which scores higher on benchmarks?
DeepSeek V4.1 Flash 1017 scores higher on the Capabilities Index (ECI): DeepSeek V4.1 Flash 1017 158.8 (#19 of 165) and DeepSeek V4.1 Flash 156.1 (#34 of 165). The confidence ranges of the top two overlap (156.7–162.2 vs 153.7–158.3), so treat the gap as small. On individual benchmarks: GPQA Diamond — DeepSeek V4.1 Flash 1017 93.2%, DeepSeek V4.1 Flash 89.8%; FrontierMath Tiers 1–3 — DeepSeek V4.1 Flash 1017 71.2%, DeepSeek V4.1 Flash 67.4%; OTIS Mock AIME 2024–2025 — DeepSeek V4.1 Flash 1017 99.4%, DeepSeek V4.1 Flash 98.3%; SimpleQA Verified — DeepSeek V4.1 Flash 42.9%, 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 DeepSeek V4.1 Flash yet, so there is no like-for-like coding score. On overall capability, DeepSeek V4.1 Flash 1017 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 DeepSeek V4.1 Flash share the same 1,000,000-token context window. Maximum output per response: DeepSeek V4.1 Flash 1017 up to 384,000, DeepSeek V4.1 Flash up to 384,000 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4.1 Flash 1017 accepts text and images; DeepSeek V4.1 Flash accepts text and images. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (MIT), so you can self-host them.
Which is newer?
DeepSeek V4.1 Flash 1017 is the newest, released Oct 17, 2026. DeepSeek V4.1 Flash came out Sep 10, 2026. Knowledge cutoff: DeepSeek V4.1 Flash 1017 May 2025, DeepSeek V4.1 Flash 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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