ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Mistral Large vs GPT-4o vs Gemma 2 27B

Too close to call on our weighted score (Mistral Large 44, GPT-4o 43, Gemma 2 27B 35). The right pick depends on what you value most.

  1. Mistral AI

    Mistral Large

    Released Feb 26, 2024

    44/100
    • ECI122.0
    • Price$0.50 / $1.50
    • Context128K
  2. OpenAI

    GPT-4o

    Released May 13, 2024

    43/100
    • ECI129.0
    • Price$2.50 / $10.00
    • Context128K
  3. Google

    Gemma 2 27B

    Released Jul 13, 2024

    35/100
    • ECI122.1
    • Price$0.65 / $0.65
    • Context8K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within a point (Mistral Large 44/100, GPT-4o 43/100, Gemma 2 27B 35/100), so choose by what matters most for your work: GPT-4o for raw capability and Gemma 2 27B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT-4oCapabilities Index (ECI): GPT-4o 129.0 · Gemma 2 27B 122.1 · Mistral Large 122.0
  • Lowest priceGemma 2 27BGemma 2 27B $0.65 · Mistral Large $0.75 · GPT-4o $4.38 per 1M tokens (3:1 blend)
  • Longest contextMistral Large and GPT-4oMistral Large 128,000 · GPT-4o 128,000 · Gemma 2 27B 8,192 tokens
  • Widest inputsGPT-4oMistral Large: Text, PDFs · GPT-4o: Text, Images, PDFs · Gemma 2 27B: Text
  • Self-hostingGemma 2 27BPublishes downloadable weights
How the score is built
MeasureWeightMistral LargeGPT-4oGemma 2 27B
CapabilityCapabilities Index (ECI)50%425142
Price25%531956
Inputs & features15%45700
Context window10%24240
Overall100%44/10043/10035/100
02 — Side by side

Every spec in one table

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

Mistral Large vs GPT-4o vs Gemma 2 27B specifications side by side
SpecificationMistral LargeMistral AIGPT-4oOpenAIGemma 2 27BGoogle
Capability
Capabilities Index (ECI)122.0129.0 (best)122.1
ECI rank#153 of 165#141 of 165 (best)#152 of 165
GPQA DiamondGraduate-level science questions38.8%48.9% (best)36.5%
OTIS Mock AIME 2024–2025Competition mathematics1.9%6.3% (best)1.4%
Price per million tokens
Input$0.50 (best)$2.50$0.65
Output$1.50$10.00$0.65 (best)
Cached input$0.05 (best)$1.25—
Blended (3:1)$0.75$4.38$0.65 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial OpenAI APIMedian of 3 providers
Limits
Context window128,000 tokens (best)128,000 tokens (best)8,192 tokens
Max output102,400 tokens (best)16,384 tokens2,048 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsYesYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesNo
Structured outputYesYesNo
Availability
WeightsProprietaryProprietaryOpen
API model IDmistral-large-latestgpt-4o—
API providers1126 (best)3
ReleasedFeb 26, 2024May 13, 2024Jul 13, 2024
Knowledge cutoffNov 30, 2024Sep 2023Jun 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$8.00
  • GPT-4o$45.00
  • Gemma 2 27B$7.80
04 — Questions

Which should you choose?

Which is better: Mistral Large, GPT-4o or Gemma 2 27B?

It is close. Our weighted score puts them within a point (Mistral Large 44/100, GPT-4o 43/100, Gemma 2 27B 35/100), so choose by what matters most for your work: GPT-4o for raw capability and Gemma 2 27B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Large, GPT-4o or Gemma 2 27B?

Gemma 2 27B is cheaper at $0.65 input / $0.65 output per million tokens (median across 3 API providers). Mistral Large costs $0.50 input / $1.50 output per million tokens (official Mistral API price); 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 $0.65 per million tokens for Gemma 2 27B versus $0.75 for Mistral Large (1.2× as much) and $4.38 for GPT-4o (6.7× as much).

Which scores higher on benchmarks?

GPT-4o scores higher on the Capabilities Index (ECI): GPT-4o 129.0 (#141 of 165), Gemma 2 27B 122.1 (#152 of 165) and Mistral Large 122.0 (#153 of 165). Their confidence ranges do not overlap (124.7–131.3 vs 115.8–124.1), so the gap is a real one. On individual benchmarks: GPQA Diamond — GPT-4o 48.9%, Mistral Large 38.8%, Gemma 2 27B 36.5%; OTIS Mock AIME 2024–2025 — GPT-4o 6.3%, Mistral Large 1.9%, Gemma 2 27B 1.4%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Large, GPT-4o and Gemma 2 27B 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. Note that Gemma 2 27B does not support tool calling, which most coding agents need.

Which has the bigger context window?

Mistral Large and GPT-4o have the largest context windows (128,000 and 128,000 tokens), against 8,192 for Gemma 2 27B. Maximum output per response: Mistral Large up to 102,400, GPT-4o up to 16,384, Gemma 2 27B up to 2,048 tokens.

Which can read images, PDFs, audio or video?

Mistral Large accepts text and PDFs; GPT-4o accepts text, images and PDFs; Gemma 2 27B accepts text. GPT-4o handles the widest range of inputs.

Are any of these open source?

Gemma 2 27B publishes its weights and can be self-hosted; Mistral Large and GPT-4o is proprietary.

Which is newer?

Gemma 2 27B is the newest, released Jul 13, 2024. GPT-4o came out May 13, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Mistral Large Nov 30, 2024, GPT-4o Sep 2023, Gemma 2 27B Jun 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.