ZMIME
Comparison · 2 models · Updated Nov 2, 2026

Mistral Large 2407 vs Claude Sonnet 3.5 v2

Claude Sonnet 3.5 v2 comes out ahead, 44 to 39 on our weighted score, though Mistral Large 2407 is 46% cheaper per token.

  1. Mistral AI

    Mistral Large 2407

    Released Jul 24, 2024

    39/100
    • ECI127.6
    • Price$2.00 / $6.00
    • Context131K
    Full specs Remove Mistral Large 2407
  2. Our pick

    Anthropic

    Claude Sonnet 3.5 v2

    Released Oct 22, 2024

    44/100
    • ECI133.4
    • Price$2.80 / $14.00
    • Context200K
    Full specs Remove Claude Sonnet 3.5 v2

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Claude Sonnet 3.5 v2 is our pick

Claude Sonnet 3.5 v2 is the better all-round choice, scoring 44/100 against Mistral Large 2407 (39). It leads on capability, inputs & features and context window. Mistral Large 2407 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityClaude Sonnet 3.5 v2Capabilities Index (ECI): Claude Sonnet 3.5 v2 133.4 · Mistral Large 2407 127.6
  • Lowest priceMistral Large 2407Mistral Large 2407 $3.00 · Claude Sonnet 3.5 v2 $5.60 per 1M tokens (3:1 blend)
  • Longest contextClaude Sonnet 3.5 v2Claude Sonnet 3.5 v2 200,000 · Mistral Large 2407 131,072 tokens
  • Widest inputsClaude Sonnet 3.5 v2Mistral Large 2407: Text, PDFs · Claude Sonnet 3.5 v2: Text, Images, PDFs
  • Self-hostingMistral Large 2407Publishes downloadable weights
How the score is built
MeasureWeightMistral Large 2407Claude Sonnet 3.5 v2
CapabilityCapabilities Index (ECI)50%4956
Price25%2614
Inputs & features15%3560
Context window10%2532
Overall100%39/10044/100
02 — Side by side

Every spec in one table

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

Mistral Large 2407 vs Claude Sonnet 3.5 v2 specifications side by side
SpecificationMistral Large 2407Mistral AIClaude Sonnet 3.5 v2Anthropic
Capability
Capabilities Index (ECI)127.6133.4 (best)
ECI rank#144 of 165#133 of 165 (best)
GPQA DiamondGraduate-level science questions49.0%55.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics8.5%8.5%
Price per million tokens
Input$2.00 (best)$2.80
Output$6.00 (best)$14.00
Cached input——
Blended (3:1)$3.00 (best)$5.60
Long-context rateSame rateSame rate
Price sourceMedian of 5 providersMedian of 2 providers
Limits
Context window131,072 tokens200,000 tokens (best)
Max output104,857 tokens (best)8,192 tokens
Inputs and features
TextYesYes
ImagesNoYes
PDFsYesYes
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenProprietary
API model ID——
API providers5 (best)3
ReleasedJul 24, 2024Oct 22, 2024
Knowledge cutoffMar 31, 2024Apr 30, 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.

  • Mistral Large 2407$32.00
  • Claude Sonnet 3.5 v2$56.00
04 — Questions

Which should you choose?

Which is better: Mistral Large 2407 or Claude Sonnet 3.5 v2?

Claude Sonnet 3.5 v2 is the better all-round choice, scoring 44/100 against Mistral Large 2407 (39). It leads on capability, inputs & features and context window. Mistral Large 2407 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Large 2407 or Claude Sonnet 3.5 v2?

Mistral Large 2407 is cheaper at $2.00 input / $6.00 output per million tokens (median across 5 API providers). Claude Sonnet 3.5 v2 costs $2.80 input / $14.00 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Mistral Large 2407 versus $5.60 for Claude Sonnet 3.5 v2 (1.9× as much).

Which scores higher on benchmarks?

Claude Sonnet 3.5 v2 scores higher on the Capabilities Index (ECI): Claude Sonnet 3.5 v2 133.4 (#133 of 165) and Mistral Large 2407 127.6 (#144 of 165). The confidence ranges of the top two overlap (128.5–137.7 vs 123.3–129.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Claude Sonnet 3.5 v2 55.3%, Mistral Large 2407 49.0%; OTIS Mock AIME 2024–2025 — Mistral Large 2407 8.5%, Claude Sonnet 3.5 v2 8.5%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Large 2407 and Claude Sonnet 3.5 v2 yet, so there is no like-for-like coding score. On overall capability, Claude Sonnet 3.5 v2 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 Sonnet 3.5 v2 has the largest context window at 200,000 tokens, against 131,072 for Mistral Large 2407. Maximum output per response: Mistral Large 2407 up to 104,857, Claude Sonnet 3.5 v2 up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Mistral Large 2407 accepts text and PDFs; Claude Sonnet 3.5 v2 accepts text, images and PDFs. Claude Sonnet 3.5 v2 handles the widest range of inputs.

Are any of these open source?

Mistral Large 2407 publishes its weights and can be self-hosted; Claude Sonnet 3.5 v2 is proprietary.

Which is newer?

Claude Sonnet 3.5 v2 is the newest, released Oct 22, 2024. Mistral Large 2407 came out Jul 24, 2024. Knowledge cutoff: Mistral Large 2407 Mar 31, 2024, Claude Sonnet 3.5 v2 Apr 30, 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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