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Comparison · 2 models · Updated Oct 4, 2026

Qwen2.5 72B Instruct vs Mixtral 8x7B

Too close to call on our weighted score (Qwen2.5 72B Instruct 40, Mixtral 8x7B 37). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen2.5 72B Instruct

    Released Sep 19, 2024

    40/100
    • ECI129.0
    • Price$1.40 / $5.60
    • Context131K
    Full specs Remove Qwen2.5 72B 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

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01 — Verdict

Too close to call

It is close. Our weighted score puts them within 3 points (Qwen2.5 72B Instruct 40/100, Mixtral 8x7B 37/100), so choose by what matters most for your work: Qwen2.5 72B Instruct for raw capability and Mixtral 8x7B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen2.5 72B InstructCapabilities Index (ECI): Qwen2.5 72B Instruct 129.0 · Mixtral 8x7B 118.5
  • Lowest priceMixtral 8x7BMixtral 8x7B $0.70 · Qwen2.5 72B Instruct $2.45 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 72B InstructQwen2.5 72B Instruct 131,072 · Mixtral 8x7B 32,000 tokens
  • Widest inputsSame inputsQwen2.5 72B 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 72B InstructMixtral 8x7B
CapabilityCapabilities Index (ECI)50%5238
Price25%3157
Inputs & features15%2525
Context window10%240
Overall100%40/10037/100
02 — Side by side

Every spec in one table

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

Qwen2.5 72B Instruct vs Mixtral 8x7B specifications side by side
SpecificationQwen2.5 72B InstructAlibaba (Qwen)Mixtral 8x7BMistral AI
Capability
Capabilities Index (ECI)129.0 (best)118.5
ECI rank#128 of 148 (best)#142 of 148
GPQA DiamondGraduate-level science questions49.2% (best)30.6%
OTIS Mock AIME 2024–2025Competition mathematics8.1%—
Price per million tokens
Input$1.40$0.70 (best)
Output$5.60$0.70 (best)
Cached input——
Blended (3:1)$2.45$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 IDqwen2-5-72b-instructopen-mixtral-8x7b
API providers11
ReleasedSep 19, 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 72B Instruct$25.20
  • Mixtral 8x7B$8.40
04 — Questions

Which should you choose?

Which is better: Qwen2.5 72B Instruct or Mixtral 8x7B?

It is close. Our weighted score puts them within 3 points (Qwen2.5 72B Instruct 40/100, Mixtral 8x7B 37/100), so choose by what matters most for your work: Qwen2.5 72B Instruct for raw capability and Mixtral 8x7B on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen2.5 72B Instruct or Mixtral 8x7B?

Mixtral 8x7B is cheaper at $0.70 input / $0.70 output per million tokens (official Mistral API price). Qwen2.5 72B Instruct costs $1.40 input / $5.60 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 $2.45 for Qwen2.5 72B Instruct (3.5× as much).

Which scores higher on benchmarks?

Qwen2.5 72B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 72B Instruct 129.0 (#128 of 148) and Mixtral 8x7B 118.5 (#142 of 148). Their confidence ranges do not overlap (123.8–130.7 vs 111.3–121.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen2.5 72B Instruct 49.2%, Mixtral 8x7B 30.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen2.5 72B Instruct and Mixtral 8x7B yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 72B 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 72B Instruct has the largest context window at 131,072 tokens, against 32,000 for Mixtral 8x7B. Maximum output per response: Qwen2.5 72B Instruct up to 8,192, Mixtral 8x7B up to 32,000 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5 72B 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 72B Instruct is the newest, released Sep 19, 2024. Mixtral 8x7B came out Dec 11, 2023. Knowledge cutoff: Qwen2.5 72B 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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