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Comparison · 2 models · Updated Oct 4, 2026

Mistral Nemo vs Qwen2.5 72B Instruct

Mistral Nemo comes out ahead, 48 to 40 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Mistral AI

    Mistral Nemo

    Released Jul 1, 2024

    48/100
    • ECI118.7
    • Price$0.15 / $0.15
    • Context128K
    Full specs Remove Mistral Nemo

  2. 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

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Mistral Nemo is our pick

Mistral Nemo is the better all-round choice, scoring 48/100 against Qwen2.5 72B Instruct (40). It leads on price. Qwen2.5 72B Instruct wins on capability. 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 · Mistral Nemo 118.7
  • Lowest priceMistral NemoMistral Nemo $0.15 · Qwen2.5 72B Instruct $2.45 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 72B InstructQwen2.5 72B Instruct 131,072 · Mistral Nemo 128,000 tokens
  • Widest inputsSame inputsMistral Nemo: Text · Qwen2.5 72B Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMistral NemoQwen2.5 72B Instruct
CapabilityCapabilities Index (ECI)50%3952
Price25%8931
Inputs & features15%2525
Context window10%2424
Overall100%48/10040/100
02 — Side by side

Every spec in one table

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

Mistral Nemo vs Qwen2.5 72B Instruct specifications side by side
SpecificationMistral NemoMistral AIQwen2.5 72B InstructAlibaba (Qwen)
Capability
Capabilities Index (ECI)118.7129.0 (best)
ECI rank#140 of 148#128 of 148 (best)
GPQA DiamondGraduate-level science questions29.9%49.2% (best)
OTIS Mock AIME 2024–2025Competition mathematics—8.1%
Price per million tokens
Input$0.15 (best)$1.40
Output$0.15 (best)$5.60
Cached input——
Blended (3:1)$0.15 (best)$2.45
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial Alibaba API
Limits
Context window128,000 tokens131,072 tokens (best)
Max output128,000 tokens (best)8,192 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDmistral-nemoqwen2-5-72b-instruct
API providers5 (best)1
ReleasedJul 1, 2024Sep 19, 2024
Knowledge cutoffJul 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.

  • Mistral Nemo$1.80
  • Qwen2.5 72B Instruct$25.20
04 — Questions

Which should you choose?

Which is better: Mistral Nemo or Qwen2.5 72B Instruct?

Mistral Nemo is the better all-round choice, scoring 48/100 against Qwen2.5 72B Instruct (40). It leads on price. Qwen2.5 72B Instruct wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Nemo or Qwen2.5 72B Instruct?

Mistral Nemo is cheaper at $0.15 input / $0.15 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 $0.15 per million tokens for Mistral Nemo versus $2.45 for Qwen2.5 72B Instruct (16× 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 Mistral Nemo 118.7 (#140 of 148). Their confidence ranges do not overlap (123.8–130.7 vs 111.3–121.5), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen2.5 72B Instruct 49.2%, Mistral Nemo 29.9%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Nemo and Qwen2.5 72B Instruct 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 128,000 for Mistral Nemo. Maximum output per response: Mistral Nemo up to 128,000, Qwen2.5 72B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Mistral Nemo accepts text; Qwen2.5 72B 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 72B Instruct is the newest, released Sep 19, 2024. Mistral Nemo came out Jul 1, 2024. Knowledge cutoff: Mistral Nemo Jul 2024, Qwen2.5 72B 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

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