ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Mistral Large 2407 vs Mistral Large 2.1 vs GPT-4o

GPT-4o comes out ahead, 43 to 39 and 38 on our weighted score, though Mistral Large 2407 is 31% 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. 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. Our pick

    OpenAI

    GPT-4o

    Released May 13, 2024

    43/100
    • ECI129.0
    • Price$2.50 / $10.00
    • Context128K
    Full specs Remove GPT-4o
01 — Verdict

GPT-4o is our pick

GPT-4o is the better all-round choice, scoring 43/100 against Mistral Large 2407 (39) and Mistral Large 2.1 (38). It leads on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-4oCapabilities Index (ECI): GPT-4o 129.0 · Mistral Large 2.1 128.6 · Mistral Large 2407 127.6
  • Lowest priceMistral Large 2407 and Mistral Large 2.1Mistral Large 2407 $3.00 · Mistral Large 2.1 $3.00 · GPT-4o $4.38 per 1M tokens (3:1 blend)
  • Longest contextMistral Large 2407 and Mistral Large 2.1Mistral Large 2407 131,072 · Mistral Large 2.1 131,072 · GPT-4o 128,000 tokens
  • Widest inputsGPT-4oMistral Large 2407: Text, PDFs · Mistral Large 2.1: Text · GPT-4o: Text, Images, PDFs
  • Self-hostingMistral Large 2407 and Mistral Large 2.1Publishes downloadable weights
How the score is built
MeasureWeightMistral Large 2407Mistral Large 2.1GPT-4o
CapabilityCapabilities Index (ECI)50%495051
Price25%262619
Inputs & features15%352570
Context window10%252524
Overall100%39/10038/10043/100
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 Mistral Large 2.1 vs GPT-4o specifications side by side
SpecificationMistral Large 2407Mistral AIMistral Large 2.1Mistral AIGPT-4oOpenAI
Capability
Capabilities Index (ECI)127.6128.6129.0 (best)
ECI rank#144 of 165#142 of 165#141 of 165 (best)
GPQA DiamondGraduate-level science questions49.0%51.3% (best)48.9%
OTIS Mock AIME 2024–2025Competition mathematics8.5% (best)7.8%6.3%
Price per million tokens
Input$2.00 (best)$2.00 (best)$2.50
Output$6.00 (best)$6.00 (best)$10.00
Cached input——$1.25
Blended (3:1)$3.00 (best)$3.00 (best)$4.38
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 5 providersMedian of 2 providersOfficial OpenAI API
Limits
Context window131,072 tokens (best)131,072 tokens (best)128,000 tokens
Max output104,857 tokens (best)16,384 tokens16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsYesNoYes
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenProprietary
API model ID——gpt-4o
API providers5226 (best)
ReleasedJul 24, 2024Nov 18, 2024May 13, 2024
Knowledge cutoffMar 31, 2024Nov 2024Sep 2023
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
  • Mistral Large 2.1$32.00
  • GPT-4o$45.00
04 — Questions

Which should you choose?

Which is better: Mistral Large 2407, Mistral Large 2.1 or GPT-4o?

GPT-4o is the better all-round choice, scoring 43/100 against Mistral Large 2407 (39) and Mistral Large 2.1 (38). It leads on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Large 2407, Mistral Large 2.1 or GPT-4o?

Mistral Large 2407 is cheaper at $2.00 input / $6.00 output per million tokens (median across 5 API providers). Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (median across 2 API providers); GPT-4o costs $2.50 input / $10.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Mistral Large 2407 versus $3.00 for Mistral Large 2.1 (1× as much) and $4.38 for GPT-4o (1.5× as much).

Which scores higher on benchmarks?

GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#141 of 165), Mistral Large 2.1 128.6 (#142 of 165) and Mistral Large 2407 127.6 (#144 of 165). The confidence ranges of the top two overlap (124.7–131.3 vs 124.3–130.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Mistral Large 2407 49.0%, GPT-4o 48.9%; OTIS Mock AIME 2024–2025 — Mistral Large 2407 8.5%, Mistral Large 2.1 7.8%, GPT-4o 6.3%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Large 2407, Mistral Large 2.1 and GPT-4o yet, so there is no like-for-like coding score. On overall capability, GPT-4o leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

Mistral Large 2407 and Mistral Large 2.1 have the largest context windows (131,072 and 131,072 tokens), against 128,000 for GPT-4o. Maximum output per response: Mistral Large 2407 up to 104,857, Mistral Large 2.1 up to 16,384, GPT-4o up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Mistral Large 2407 accepts text and PDFs; Mistral Large 2.1 accepts text; GPT-4o accepts text, images and PDFs. GPT-4o handles the widest range of inputs.

Are any of these open source?

Mistral Large 2407 and Mistral Large 2.1 publishes its weights and can be self-hosted; GPT-4o is proprietary.

Which is newer?

Mistral Large 2.1 is the newest, released Nov 18, 2024. Mistral Large 2407 came out Jul 24, 2024; GPT-4o came out May 13, 2024. Knowledge cutoff: Mistral Large 2407 Mar 31, 2024, Mistral Large 2.1 Nov 2024, GPT-4o Sep 2023.

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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