ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Mixtral 8x7B vs Qwen2.5 32B Instruct

Qwen2.5 32B Instruct comes out ahead, 43 to 37 on our weighted score, though Mixtral 8x7B is 43% cheaper per token.

  1. Mistral AI

    Mixtral 8x7B

    Released Dec 11, 2023

    37/100
    • ECI118.5
    • Price$0.70 / $0.70
    • Context32K
    Full specs Remove Mixtral 8x7B
  2. Our pick

    Alibaba (Qwen)

    Qwen2.5 32B Instruct

    Released Sep 17, 2024

    43/100
    • ECI128.5
    • Price$0.70 / $2.80
    • Context131K
    Full specs Remove Qwen2.5 32B Instruct

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen2.5 32B Instruct is our pick

Qwen2.5 32B Instruct is the better all-round choice, scoring 43/100 against Mixtral 8x7B (37). It leads on capability and context window. Mixtral 8x7B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen2.5 32B InstructCapabilities Index (ECI): Qwen2.5 32B Instruct 128.5 · Mixtral 8x7B 118.5
  • Lowest priceMixtral 8x7BMixtral 8x7B $0.70 · Qwen2.5 32B Instruct $1.23 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 32B InstructQwen2.5 32B Instruct 131,072 · Mixtral 8x7B 32,000 tokens
  • Widest inputsSame inputsMixtral 8x7B: Text · Qwen2.5 32B Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMixtral 8x7BQwen2.5 32B Instruct
CapabilityCapabilities Index (ECI)50%3851
Price25%5746
Inputs & features15%2525
Context window10%024
Overall100%37/10043/100
02 — Side by side

Every spec in one table

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

Mixtral 8x7B vs Qwen2.5 32B Instruct specifications side by side
SpecificationMixtral 8x7BMistral AIQwen2.5 32B InstructAlibaba (Qwen)
Capability
Capabilities Index (ECI)118.5128.5 (best)
ECI rank#142 of 148#131 of 148 (best)
GPQA DiamondGraduate-level science questions30.6%46.1% (best)
OTIS Mock AIME 2024–2025Competition mathematics—7.4%
Price per million tokens
Input$0.70$0.70
Output$0.70 (best)$2.80
Cached input——
Blended (3:1)$0.70 (best)$1.23
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial Alibaba API
Limits
Context window32,000 tokens131,072 tokens (best)
Max output32,000 tokens (best)8,192 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDopen-mixtral-8x7bqwen2-5-32b-instruct
API providers11
ReleasedDec 11, 2023Sep 17, 2024
Knowledge cutoffJan 2024Apr 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.

  • Mixtral 8x7B$8.40
  • Qwen2.5 32B Instruct$12.60
04 — Questions

Which should you choose?

Which is better: Mixtral 8x7B or Qwen2.5 32B Instruct?

Qwen2.5 32B Instruct is the better all-round choice, scoring 43/100 against Mixtral 8x7B (37). It leads on capability and context window. Mixtral 8x7B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mixtral 8x7B or Qwen2.5 32B Instruct?

Mixtral 8x7B is cheaper at $0.70 input / $0.70 output per million tokens (official Mistral API price). Qwen2.5 32B Instruct costs $0.70 input / $2.80 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.70 per million tokens for Mixtral 8x7B versus $1.23 for Qwen2.5 32B Instruct (1.8× as much).

Which scores higher on benchmarks?

Qwen2.5 32B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 32B Instruct 128.5 (#131 of 148) and Mixtral 8x7B 118.5 (#142 of 148). Their confidence ranges do not overlap (123.5–130.0 vs 111.3–121.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen2.5 32B Instruct 46.1%, Mixtral 8x7B 30.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Mixtral 8x7B and Qwen2.5 32B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 32B Instruct leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

Qwen2.5 32B Instruct has the largest context window at 131,072 tokens, against 32,000 for Mixtral 8x7B. Maximum output per response: Mixtral 8x7B up to 32,000, Qwen2.5 32B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Mixtral 8x7B accepts text; Qwen2.5 32B Instruct accepts text. They handle the same number of input types.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

Qwen2.5 32B Instruct is the newest, released Sep 17, 2024. Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Mixtral 8x7B Jan 2024, Qwen2.5 32B Instruct Apr 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 Oct 4, 2026.

05 — Keep comparing

Related comparisons