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Comparison · 3 models · Updated Nov 2, 2026

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

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. Google

    Gemma 2 27B

    Released Jul 13, 2024

    35/100
    • ECI122.1
    • Price$0.65 / $0.65
    • Context8K
  2. OpenAI

    GPT-4o

    Released May 13, 2024

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

    Mistral Large

    Released Feb 26, 2024

    44/100
    • ECI122.0
    • Price$0.50 / $1.50
    • Context128K
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 contextGPT-4o and Mistral LargeGPT-4o 128,000 · Mistral Large 128,000 · Gemma 2 27B 8,192 tokens
  • Widest inputsGPT-4oGemma 2 27B: Text · GPT-4o: Text, Images, PDFs · Mistral Large: Text, PDFs
  • Self-hostingGemma 2 27BPublishes downloadable weights
How the score is built
MeasureWeightGemma 2 27BGPT-4oMistral Large
CapabilityCapabilities Index (ECI)50%425142
Price25%561953
Inputs & features15%07045
Context window10%02424
Overall100%35/10043/10044/100
02 — Side by side

Every spec in one table

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

Gemma 2 27B vs GPT-4o vs Mistral Large specifications side by side
SpecificationGemma 2 27BGoogleGPT-4oOpenAIMistral LargeMistral AI
Capability
Capabilities Index (ECI)122.1129.0 (best)122.0
ECI rank#152 of 165#141 of 165 (best)#153 of 165
GPQA DiamondGraduate-level science questions36.5%48.9% (best)38.8%
OTIS Mock AIME 2024–2025Competition mathematics1.4%6.3% (best)1.9%
Price per million tokens
Input$0.65$2.50$0.50 (best)
Output$0.65 (best)$10.00$1.50
Cached input—$1.25$0.05 (best)
Blended (3:1)$0.65 (best)$4.38$0.75
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 3 providersOfficial OpenAI APIOfficial Mistral API
Limits
Context window8,192 tokens128,000 tokens (best)128,000 tokens (best)
Max output2,048 tokens16,384 tokens102,400 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoYesYes
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingNoYesYes
Structured outputNoYesYes
Availability
WeightsOpenProprietaryProprietary
API model ID—gpt-4omistral-large-latest
API providers326 (best)11
ReleasedJul 13, 2024May 13, 2024Feb 26, 2024
Knowledge cutoffJun 30, 2024Sep 2023Nov 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.

  • Gemma 2 27B$7.80
  • GPT-4o$45.00
  • Mistral Large$8.00
04 — Questions

Which should you choose?

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

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

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 Gemma 2 27B, GPT-4o and Mistral Large 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?

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

Which can read images, PDFs, audio or video?

Gemma 2 27B accepts text; GPT-4o accepts text, images and PDFs; Mistral Large accepts text and PDFs. 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; GPT-4o and Mistral Large 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: Gemma 2 27B Jun 30, 2024, GPT-4o Sep 2023, Mistral Large Nov 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.