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Comparison · 3 models · Updated Nov 2, 2026

GPT-4o vs Mixtral 8x22B Instruct vs Mistral Large 2407

GPT-4o comes out ahead, 43 to 39 and 34 on our weighted score, though Mixtral 8x22B Instruct is 31% cheaper per token.

  1. Our pick

    OpenAI

    GPT-4o

    Released May 13, 2024

    43/100
    • ECI129.0
    • Price$2.50 / $10.00
    • Context128K
  2. Mistral AI

    Mixtral 8x22B Instruct

    Released Apr 17, 2024

    34/100
    • ECI122.0
    • Price$2.00 / $6.00
    • Context66K
  3. Mistral AI

    Mistral Large 2407

    Released Jul 24, 2024

    39/100
    • ECI127.6
    • Price$2.00 / $6.00
    • Context131K
01 — Verdict

GPT-4o is our pick

GPT-4o is the better all-round choice, scoring 43/100 against Mistral Large 2407 (39) and Mixtral 8x22B Instruct (34). It leads on capability and 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 2407 127.6 · Mixtral 8x22B Instruct 122.0
  • Lowest priceMixtral 8x22B Instruct and Mistral Large 2407Mixtral 8x22B Instruct $3.00 · Mistral Large 2407 $3.00 · GPT-4o $4.38 per 1M tokens (3:1 blend)
  • Longest contextMistral Large 2407Mistral Large 2407 131,072 · GPT-4o 128,000 · Mixtral 8x22B Instruct 65,536 tokens
  • Widest inputsGPT-4oGPT-4o: Text, Images, PDFs · Mixtral 8x22B Instruct: Text, PDFs · Mistral Large 2407: Text, PDFs
  • Self-hostingMixtral 8x22B Instruct and Mistral Large 2407Publishes downloadable weights
How the score is built
MeasureWeightGPT-4oMixtral 8x22B InstructMistral Large 2407
CapabilityCapabilities Index (ECI)50%514249
Price25%192626
Inputs & features15%703535
Context window10%241225
Overall100%43/10034/10039/100
02 — Side by side

Every spec in one table

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

GPT-4o vs Mixtral 8x22B Instruct vs Mistral Large 2407 specifications side by side
SpecificationGPT-4oOpenAIMixtral 8x22B InstructMistral AIMistral Large 2407Mistral AI
Capability
Capabilities Index (ECI)129.0 (best)122.0127.6
ECI rank#141 of 165 (best)#155 of 165#144 of 165
GPQA DiamondGraduate-level science questions48.9%34.1%49.0% (best)
OTIS Mock AIME 2024–2025Competition mathematics6.3%—8.5% (best)
Price per million tokens
Input$2.50$2.00 (best)$2.00 (best)
Output$10.00$6.00 (best)$6.00 (best)
Cached input$1.25——
Blended (3:1)$4.38$3.00 (best)$3.00 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial OpenAI APIMedian of 5 providersMedian of 5 providers
Limits
Context window128,000 tokens65,536 tokens131,072 tokens (best)
Max output16,384 tokens52,428 tokens104,857 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoNo
PDFsYesYesYes
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsProprietaryOpenOpen
API model IDgpt-4o——
API providers26 (best)55
ReleasedMay 13, 2024Apr 17, 2024Jul 24, 2024
Knowledge cutoffSep 2023Jan 31, 2024Mar 31, 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.

  • GPT-4o$45.00
  • Mixtral 8x22B Instruct$32.00
  • Mistral Large 2407$32.00
04 — Questions

Which should you choose?

Which is better: GPT-4o, Mixtral 8x22B Instruct or Mistral Large 2407?

GPT-4o is the better all-round choice, scoring 43/100 against Mistral Large 2407 (39) and Mixtral 8x22B Instruct (34). It leads on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT-4o, Mixtral 8x22B Instruct or Mistral Large 2407?

Mixtral 8x22B Instruct is cheaper at $2.00 input / $6.00 output per million tokens (median across 5 API providers). Mistral Large 2407 costs $2.00 input / $6.00 output per million tokens (median across 5 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 Mixtral 8x22B Instruct versus $3.00 for Mistral Large 2407 (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 2407 127.6 (#144 of 165) and Mixtral 8x22B Instruct 122.0 (#155 of 165). The confidence ranges of the top two overlap (124.7–131.3 vs 123.3–129.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2407 49.0%, GPT-4o 48.9%, Mixtral 8x22B Instruct 34.1%.

Which is better for coding?

There are no published SWE-bench Verified results for GPT-4o, Mixtral 8x22B Instruct and Mistral Large 2407 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 has the largest context window at 131,072 tokens, against 128,000 for GPT-4o and 65,536 for Mixtral 8x22B Instruct. Maximum output per response: GPT-4o up to 16,384, Mixtral 8x22B Instruct up to 52,428, Mistral Large 2407 up to 104,857 tokens.

Which can read images, PDFs, audio or video?

GPT-4o accepts text, images and PDFs; Mixtral 8x22B Instruct accepts text and PDFs; Mistral Large 2407 accepts text and PDFs. GPT-4o handles the widest range of inputs.

Are any of these open source?

Mixtral 8x22B Instruct and Mistral Large 2407 publishes its weights and can be self-hosted; GPT-4o is proprietary.

Which is newer?

Mistral Large 2407 is the newest, released Jul 24, 2024. GPT-4o came out May 13, 2024; Mixtral 8x22B Instruct came out Apr 17, 2024. Knowledge cutoff: GPT-4o Sep 2023, Mixtral 8x22B Instruct Jan 31, 2024, Mistral Large 2407 Mar 31, 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.