ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Mistral Large vs Mistral Large 2407 vs Gemma 2 27B

Mistral Large comes out ahead, 44 to 39 and 35 on our weighted score, though Gemma 2 27B is 13% cheaper per token.

  1. Our pick

    Mistral AI

    Mistral Large

    Released Feb 26, 2024

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

    Mistral Large 2407

    Released Jul 24, 2024

    39/100
    • ECI127.6
    • Price$2.00 / $6.00
    • Context131K
  3. Google

    Gemma 2 27B

    Released Jul 13, 2024

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

Mistral Large is our pick

Mistral Large is the better all-round choice, scoring 44/100 against Mistral Large 2407 (39) and Gemma 2 27B (35). It leads on inputs & features. Mistral Large 2407 wins on capability. Gemma 2 27B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMistral Large 2407Capabilities Index (ECI): Mistral Large 2407 127.6 · Gemma 2 27B 122.1 · Mistral Large 122.0
  • Lowest priceGemma 2 27BGemma 2 27B $0.65 · Mistral Large $0.75 · Mistral Large 2407 $3.00 per 1M tokens (3:1 blend)
  • Longest contextMistral Large 2407Mistral Large 2407 131,072 · Mistral Large 128,000 · Gemma 2 27B 8,192 tokens
  • Widest inputsMistral Large and Mistral Large 2407Mistral Large: Text, PDFs · Mistral Large 2407: Text, PDFs · Gemma 2 27B: Text
  • Self-hostingMistral Large 2407 and Gemma 2 27BPublishes downloadable weights
How the score is built
MeasureWeightMistral LargeMistral Large 2407Gemma 2 27B
CapabilityCapabilities Index (ECI)50%424942
Price25%532656
Inputs & features15%45350
Context window10%24250
Overall100%44/10039/10035/100
02 — Side by side

Every spec in one table

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

Mistral Large vs Mistral Large 2407 vs Gemma 2 27B specifications side by side
SpecificationMistral LargeMistral AIMistral Large 2407Mistral AIGemma 2 27BGoogle
Capability
Capabilities Index (ECI)122.0127.6 (best)122.1
ECI rank#153 of 165#144 of 165 (best)#152 of 165
GPQA DiamondGraduate-level science questions38.8%49.0% (best)36.5%
OTIS Mock AIME 2024–2025Competition mathematics1.9%8.5% (best)1.4%
Price per million tokens
Input$0.50 (best)$2.00$0.65
Output$1.50$6.00$0.65 (best)
Cached input$0.05——
Blended (3:1)$0.75$3.00$0.65 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 5 providersMedian of 3 providers
Limits
Context window128,000 tokens131,072 tokens (best)8,192 tokens
Max output102,400 tokens104,857 tokens (best)2,048 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsYesYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesNo
Structured outputYesNoNo
Availability
WeightsProprietaryOpenOpen
API model IDmistral-large-latest——
API providers11 (best)53
ReleasedFeb 26, 2024Jul 24, 2024Jul 13, 2024
Knowledge cutoffNov 30, 2024Mar 31, 2024Jun 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
  • Mistral Large 2407$32.00
  • Gemma 2 27B$7.80
04 — Questions

Which should you choose?

Which is better: Mistral Large, Mistral Large 2407 or Gemma 2 27B?

Mistral Large is the better all-round choice, scoring 44/100 against Mistral Large 2407 (39) and Gemma 2 27B (35). It leads on inputs & features. Mistral Large 2407 wins on capability. Gemma 2 27B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Large, Mistral Large 2407 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); Mistral Large 2407 costs $2.00 input / $6.00 output per million tokens (median across 5 API providers). 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 $3.00 for Mistral Large 2407 (4.6× as much).

Which scores higher on benchmarks?

Mistral Large 2407 scores higher on the Capabilities Index (ECI): Mistral Large 2407 127.6 (#144 of 165), Gemma 2 27B 122.1 (#152 of 165) and Mistral Large 122.0 (#153 of 165). The confidence ranges of the top two overlap (123.3–129.4 vs 115.8–124.1), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2407 49.0%, Mistral Large 38.8%, Gemma 2 27B 36.5%; OTIS Mock AIME 2024–2025 — Mistral Large 2407 8.5%, 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, Mistral Large 2407 and Gemma 2 27B yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2407 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 2407 has the largest context window at 131,072 tokens, against 128,000 for Mistral Large and 8,192 for Gemma 2 27B. Maximum output per response: Mistral Large up to 102,400, Mistral Large 2407 up to 104,857, Gemma 2 27B up to 2,048 tokens.

Which can read images, PDFs, audio or video?

Mistral Large accepts text and PDFs; Mistral Large 2407 accepts text and PDFs; Gemma 2 27B accepts text. Mistral Large handles the widest range of inputs.

Are any of these open source?

Mistral Large 2407 and Gemma 2 27B publishes its weights and can be self-hosted; Mistral Large is proprietary.

Which is newer?

Mistral Large 2407 is the newest, released Jul 24, 2024. Gemma 2 27B came out Jul 13, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Mistral Large Nov 30, 2024, Mistral Large 2407 Mar 31, 2024, 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.