ZMIME
Comparison · 3 models · Updated Nov 2, 2026

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

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

  1. Google

    Gemma 2 27B

    Released Jul 13, 2024

    32/100
    • ECI122.1
    • Price$0.65 / $0.65
    • Context8K
  2. Our pick

    Mistral AI

    Mistral Large

    Released Feb 26, 2024

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

    WizardLM 2 8x22B

    Released Apr 15, 2024

    38/100
    • ECI—
    • Price$0.493 / $0.493
    • Context66K
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 LargeGemma 2 27B: Text · Mistral Large: Text, PDFs · WizardLM 2 8x22B: Text
  • Self-hostingGemma 2 27B and WizardLM 2 8x22BPublishes downloadable weights (Apache-2.0)
How the score is built
MeasureWeightGemma 2 27BMistral LargeWizardLM 2 8x22B
CapabilityShared benchmarks50%363943
Price25%565362
Inputs & features15%0450
Context window10%02412
Overall100%32/10042/10038/100
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 Mistral Large vs WizardLM 2 8x22B specifications side by side
SpecificationGemma 2 27BGoogleMistral LargeMistral AIWizardLM 2 8x22BMicrosoft
Capability
Capabilities Index (ECI)122.1 (best)122.0—
ECI rank#152 of 165 (best)#153 of 165—
GPQA DiamondGraduate-level science questions36.5%38.8%43.4% (best)
OTIS Mock AIME 2024–2025Competition mathematics1.4%1.9% (best)—
Price per million tokens
Input$0.65$0.50$0.493 (best)
Output$0.65$1.50$0.493 (best)
Cached input—$0.05—
Blended (3:1)$0.65$0.75$0.493 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 3 providersOfficial Mistral APIMedian of 3 providers
Limits
Context window8,192 tokens128,000 tokens (best)65,536 tokens
Max output2,048 tokens102,400 tokens (best)8,000 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoYesNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingNoYesNo
Structured outputNoYesNo
Availability
WeightsOpenProprietaryOpenApache-2.0
API model ID—mistral-large-latest—
API providers311 (best)3
ReleasedJul 13, 2024Feb 26, 2024Apr 15, 2024
Knowledge cutoffJun 30, 2024Nov 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
  • Mistral Large$8.00
  • WizardLM 2 8x22B$5.92
04 — Questions

Which should you choose?

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

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

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 Gemma 2 27B, Mistral Large and WizardLM 2 8x22B 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 Gemma 2 27B and WizardLM 2 8x22B 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: Gemma 2 27B up to 2,048, Mistral Large up to 102,400, WizardLM 2 8x22B up to 8,000 tokens.

Which can read images, PDFs, audio or video?

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

Are any of these open source?

Gemma 2 27B and WizardLM 2 8x22B 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: Gemma 2 27B Jun 30, 2024, 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.