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Comparison · 2 models · Updated Oct 4, 2026

Qwen2.5 32B Instruct vs Mixtral 8x7B

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

  1. 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

  2. Mistral AI

    Mixtral 8x7B

    Released Dec 11, 2023

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

  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 inputsQwen2.5 32B Instruct: Text · Mixtral 8x7B: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen2.5 32B InstructMixtral 8x7B
CapabilityCapabilities Index (ECI)50%5138
Price25%4657
Inputs & features15%2525
Context window10%240
Overall100%43/10037/100
02 — Side by side

Every spec in one table

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

Qwen2.5 32B Instruct vs Mixtral 8x7B specifications side by side
SpecificationQwen2.5 32B InstructAlibaba (Qwen)Mixtral 8x7BMistral AI
Capability
Capabilities Index (ECI)128.5 (best)118.5
ECI rank#131 of 148 (best)#142 of 148
GPQA DiamondGraduate-level science questions46.1% (best)30.6%
OTIS Mock AIME 2024–2025Competition mathematics7.4%—
Price per million tokens
Input$0.70$0.70
Output$2.80$0.70 (best)
Cached input——
Blended (3:1)$1.23$0.70 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial Mistral API
Limits
Context window131,072 tokens (best)32,000 tokens
Max output8,192 tokens32,000 tokens (best)
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDqwen2-5-32b-instructopen-mixtral-8x7b
API providers11
ReleasedSep 17, 2024Dec 11, 2023
Knowledge cutoffApr 2024Jan 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.

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

Which should you choose?

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

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

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 Qwen2.5 32B Instruct and Mixtral 8x7B 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: Qwen2.5 32B Instruct up to 8,192, Mixtral 8x7B up to 32,000 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5 32B Instruct accepts text; Mixtral 8x7B 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: Qwen2.5 32B Instruct Apr 2024, Mixtral 8x7B Jan 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

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