ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Mistral Large vs WizardLM 2 8x22B vs Gemma 2 27B

Mistral Large comes out ahead, 42 to 38 and 32 on our weighted score, though WizardLM 2 8x22B is 34% cheaper per token.

  1. Our pick

    Mistral AI

    Mistral Large

    Released Feb 26, 2024

    42/100
    • ECI122.0
    • Price$0.50 / $1.50
    • Context128K
  2. Microsoft

    WizardLM 2 8x22B

    Released Apr 15, 2024

    38/100
    • ECI—
    • Price$0.493 / $0.493
    • Context66K
  3. Google

    Gemma 2 27B

    Released Jul 13, 2024

    32/100
    • ECI122.1
    • Price$0.65 / $0.65
    • Context8K
01 — Verdict

Mistral Large is our pick

Mistral Large is the better all-round choice, scoring 42/100 against WizardLM 2 8x22B (38) and Gemma 2 27B (32). It leads on inputs & features and context window. WizardLM 2 8x22B wins on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because WizardLM 2 8x22B has no Capabilities Index score yet.

  • CapabilityWizardLM 2 8x22BShared benchmarks: WizardLM 2 8x22B 43.4% · Mistral Large 38.8% · Gemma 2 27B 36.5%
  • Lowest priceWizardLM 2 8x22BWizardLM 2 8x22B $0.493 · Gemma 2 27B $0.65 · Mistral Large $0.75 per 1M tokens (3:1 blend)
  • Longest contextMistral LargeMistral Large 128,000 · WizardLM 2 8x22B 65,536 · Gemma 2 27B 8,192 tokens
  • Widest inputsMistral LargeMistral Large: Text, PDFs · WizardLM 2 8x22B: Text · Gemma 2 27B: Text
  • Self-hostingWizardLM 2 8x22B and Gemma 2 27BPublishes downloadable weights (Apache-2.0)
How the score is built
MeasureWeightMistral LargeWizardLM 2 8x22BGemma 2 27B
CapabilityShared benchmarks50%394336
Price25%536256
Inputs & features15%4500
Context window10%24120
Overall100%42/10038/10032/100
02 — Side by side

Every spec in one table

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

Mistral Large vs WizardLM 2 8x22B vs Gemma 2 27B specifications side by side
SpecificationMistral LargeMistral AIWizardLM 2 8x22BMicrosoftGemma 2 27BGoogle
Capability
Capabilities Index (ECI)122.0—122.1 (best)
ECI rank#153 of 165—#152 of 165 (best)
GPQA DiamondGraduate-level science questions38.8%43.4% (best)36.5%
OTIS Mock AIME 2024–2025Competition mathematics1.9% (best)—1.4%
Price per million tokens
Input$0.50$0.493 (best)$0.65
Output$1.50$0.493 (best)$0.65
Cached input$0.05——
Blended (3:1)$0.75$0.493 (best)$0.65
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 3 providersMedian of 3 providers
Limits
Context window128,000 tokens (best)65,536 tokens8,192 tokens
Max output102,400 tokens (best)8,000 tokens2,048 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsYesNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesNoNo
Structured outputYesNoNo
Availability
WeightsProprietaryOpenApache-2.0Open
API model IDmistral-large-latest——
API providers11 (best)33
ReleasedFeb 26, 2024Apr 15, 2024Jul 13, 2024
Knowledge cutoffNov 30, 2024—Jun 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
  • WizardLM 2 8x22B$5.92
  • Gemma 2 27B$7.80
04 — Questions

Which should you choose?

Which is better: Mistral Large, WizardLM 2 8x22B or Gemma 2 27B?

Mistral Large is the better all-round choice, scoring 42/100 against WizardLM 2 8x22B (38) and Gemma 2 27B (32). It leads on inputs & features and context window. WizardLM 2 8x22B wins on capability and price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because WizardLM 2 8x22B has no Capabilities Index score yet.

Which is cheaper, Mistral Large, WizardLM 2 8x22B or Gemma 2 27B?

WizardLM 2 8x22B is cheaper at $0.493 input / $0.493 output per million tokens (median across 3 API providers). Gemma 2 27B costs $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). At a typical mix of three input tokens to one output token, that is $0.493 per million tokens for WizardLM 2 8x22B versus $0.65 for Gemma 2 27B (1.3× as much) and $0.75 for Mistral Large (1.5× as much).

Which scores higher on benchmarks?

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): WizardLM 2 8x22B 43.4%, Mistral Large 38.8% and Gemma 2 27B 36.5%. On individual benchmarks: GPQA Diamond — WizardLM 2 8x22B 43.4%, Mistral Large 38.8%, Gemma 2 27B 36.5%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Large, WizardLM 2 8x22B and Gemma 2 27B yet, so there is no like-for-like coding score. On overall capability, WizardLM 2 8x22B leads, which tends to carry over to coding, but test on your own codebase. Note that WizardLM 2 8x22B and Gemma 2 27B does not support tool calling, which most coding agents need.

Which has the bigger context window?

Mistral Large has the largest context window at 128,000 tokens, against 65,536 for WizardLM 2 8x22B and 8,192 for Gemma 2 27B. Maximum output per response: Mistral Large up to 102,400, WizardLM 2 8x22B up to 8,000, Gemma 2 27B up to 2,048 tokens.

Which can read images, PDFs, audio or video?

Mistral Large accepts text and PDFs; WizardLM 2 8x22B accepts text; Gemma 2 27B accepts text. Mistral Large handles the widest range of inputs.

Are any of these open source?

WizardLM 2 8x22B and Gemma 2 27B publishes its weights (Apache-2.0) and can be self-hosted; Mistral Large is proprietary.

Which is newer?

Gemma 2 27B is the newest, released Jul 13, 2024. WizardLM 2 8x22B came out Apr 15, 2024; Mistral Large came out Feb 26, 2024. Knowledge cutoff: Mistral Large Nov 30, 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.