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Comparison · 2 models · Updated Nov 2, 2026

DeepSeek V4.1 Flash 1017 vs Mistral Large 2.1

DeepSeek V4.1 Flash 1017 comes out ahead, 79 to 38 on our weighted score, and it is the cheaper option too.

  1. Our pick

    DeepSeek

    DeepSeek V4.1 Flash 1017

    Released Oct 17, 2026New

    79/100
    • ECI158.8
    • Price$0.15 / $0.60
    • Context1M
    Full specs Remove DeepSeek V4.1 Flash 1017

  2. Mistral AI

    Mistral Large 2.1

    Released Nov 18, 2024

    38/100
    • ECI128.6
    • Price$2.00 / $6.00
    • Context131K
    Full specs Remove Mistral Large 2.1

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

DeepSeek V4.1 Flash 1017 is our pick

DeepSeek V4.1 Flash 1017 is the better all-round choice, scoring 79/100 against Mistral Large 2.1 (38). It leads on capability, price, inputs & features and context window. 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 · Mistral Large 2.1 128.6
  • Lowest priceDeepSeek V4.1 Flash 1017DeepSeek V4.1 Flash 1017 $0.263 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
  • Longest contextDeepSeek V4.1 Flash 1017DeepSeek V4.1 Flash 1017 1,000,000 · Mistral Large 2.1 131,072 tokens
  • Widest inputsDeepSeek V4.1 Flash 1017DeepSeek V4.1 Flash 1017: Text, Images · Mistral Large 2.1: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightDeepSeek V4.1 Flash 1017Mistral Large 2.1
CapabilityCapabilities Index (ECI)50%8750
Price25%7426
Inputs & features15%7025
Context window10%6025
Overall100%79/10038/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

DeepSeek V4.1 Flash 1017 vs Mistral Large 2.1 specifications side by side
SpecificationDeepSeek V4.1 Flash 1017DeepSeekMistral Large 2.1Mistral AI
Capability
Capabilities Index (ECI)158.8 (best)128.6
ECI rank#19 of 165 (best)#142 of 165
GPQA DiamondGraduate-level science questions93.2% (best)51.3%
FrontierMath Tiers 1–3Research-level mathematics71.2%—
OTIS Mock AIME 2024–2025Competition mathematics99.4% (best)7.8%
SimpleQA VerifiedShort factual questions42.5%—
Price per million tokens
Input$0.15 (best)$2.00
Output$0.60 (best)$6.00
Cached input$0.003—
Blended (3:1)$0.263 (best)$3.00
Long-context rateSame rateSame rate
Price sourceOfficial DeepSeek APIMedian of 2 providers
Limits
Context window1,000,000 tokens (best)131,072 tokens
Max output384,000 tokens (best)16,384 tokens
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYeslow · high · maxNo
Tool callingYesYes
Structured outputYesNo
Availability
WeightsOpenMITOpen
API model IDdeepseek-flash—
API providers40 (best)2
ReleasedOct 17, 2026Nov 18, 2024
Knowledge cutoffMay 2025Nov 2024
03 — Cost

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
  • Mistral Large 2.1$32.00
04 — Questions

Which should you choose?

Which is better: DeepSeek V4.1 Flash 1017 or Mistral Large 2.1?

DeepSeek V4.1 Flash 1017 is the better all-round choice, scoring 79/100 against Mistral Large 2.1 (38). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek V4.1 Flash 1017 or Mistral Large 2.1?

DeepSeek V4.1 Flash 1017 is cheaper at $0.15 input / $0.60 output per million tokens (official DeepSeek API price). Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (median across 2 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 $3.00 for Mistral Large 2.1 (11× 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 Mistral Large 2.1 128.6 (#142 of 165). Their confidence ranges do not overlap (156.7–162.2 vs 124.3–130.7), so the gap is a real one. On individual benchmarks: GPQA Diamond — DeepSeek V4.1 Flash 1017 93.2%, Mistral Large 2.1 51.3%; OTIS Mock AIME 2024–2025 — DeepSeek V4.1 Flash 1017 99.4%, Mistral Large 2.1 7.8%.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek V4.1 Flash 1017 and Mistral Large 2.1 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 has the largest context window at 1,000,000 tokens, against 131,072 for Mistral Large 2.1. Maximum output per response: DeepSeek V4.1 Flash 1017 up to 384,000, Mistral Large 2.1 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

DeepSeek V4.1 Flash 1017 accepts text and images; Mistral Large 2.1 accepts text. DeepSeek V4.1 Flash 1017 handles the widest range of inputs.

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. Mistral Large 2.1 came out Nov 18, 2024. Knowledge cutoff: DeepSeek V4.1 Flash 1017 May 2025, Mistral Large 2.1 Nov 2024.

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.

05 — Keep comparing

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