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Comparison · 3 models · Updated Oct 4, 2026

Mistral Nemo vs Qwen2.5 32B Instruct vs Llama-3.1-8B-Instruct

Too close to call on our weighted score (Mistral Nemo 48, Llama-3.1-8B-Instruct 46, Qwen2.5 32B Instruct 43). The right pick depends on what you value most.

  1. 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 32B Instruct

    Released Sep 17, 2024

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

  3. Meta

    Llama-3.1-8B-Instruct

    Released Jul 23, 2024

    46/100
    • ECI116.6
    • Price$0.152 / $0.167
    • Context128K
    Full specs Remove Llama-3.1-8B-Instruct
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (Mistral Nemo 48/100, Llama-3.1-8B-Instruct 46/100, Qwen2.5 32B Instruct 43/100), so choose by what matters most for your work: Qwen2.5 32B Instruct for raw capability and Mistral Nemo 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 · Mistral Nemo 118.7 · Llama-3.1-8B-Instruct 116.6
  • Lowest priceMistral NemoMistral Nemo $0.15 · Llama-3.1-8B-Instruct $0.156 · Qwen2.5 32B Instruct $1.23 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 32B InstructQwen2.5 32B Instruct 131,072 · Mistral Nemo 128,000 · Llama-3.1-8B-Instruct 128,000 tokens
  • Widest inputsSame inputsMistral Nemo: Text · Qwen2.5 32B Instruct: Text · Llama-3.1-8B-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 32B InstructLlama-3.1-8B-Instruct
CapabilityCapabilities Index (ECI)50%395136
Price25%894688
Inputs & features15%252525
Context window10%242424
Overall100%48/10043/10046/100
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 32B Instruct vs Llama-3.1-8B-Instruct specifications side by side
SpecificationMistral NemoMistral AIQwen2.5 32B InstructAlibaba (Qwen)Llama-3.1-8B-InstructMeta
Capability
Capabilities Index (ECI)118.7128.5 (best)116.6
ECI rank#140 of 148#131 of 148 (best)#145 of 148
GPQA DiamondGraduate-level science questions29.9%46.1% (best)27.0%
OTIS Mock AIME 2024–2025Competition mathematics—7.4% (best)1.7%
Price per million tokens
Input$0.15 (best)$0.70$0.152
Output$0.15 (best)$2.80$0.167
Cached input———
Blended (3:1)$0.15 (best)$1.23$0.156
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial Alibaba APIMedian of 9 providers
Limits
Context window128,000 tokens131,072 tokens (best)128,000 tokens
Max output128,000 tokens (best)8,192 tokens4,096 tokens
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model IDmistral-nemoqwen2-5-32b-instruct—
API providers519 (best)
ReleasedJul 1, 2024Sep 17, 2024Jul 23, 2024
Knowledge cutoffJul 2024Apr 2024Dec 2023
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 32B Instruct$12.60
  • Llama-3.1-8B-Instruct$1.85
04 — Questions

Which should you choose?

Which is better: Mistral Nemo, Qwen2.5 32B Instruct or Llama-3.1-8B-Instruct?

It is close. Our weighted score puts them within 2 points (Mistral Nemo 48/100, Llama-3.1-8B-Instruct 46/100, Qwen2.5 32B Instruct 43/100), so choose by what matters most for your work: Qwen2.5 32B Instruct for raw capability and Mistral Nemo on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Nemo, Qwen2.5 32B Instruct or Llama-3.1-8B-Instruct?

Mistral Nemo is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 API providers); 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 $0.15 per million tokens for Mistral Nemo versus $0.156 for Llama-3.1-8B-Instruct (1× as much) and $1.23 for Qwen2.5 32B Instruct (8.2× 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), Mistral Nemo 118.7 (#140 of 148) and Llama-3.1-8B-Instruct 116.6 (#145 of 148). Their confidence ranges do not overlap (123.5–130.0 vs 111.3–121.5), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen2.5 32B Instruct 46.1%, Mistral Nemo 29.9%, Llama-3.1-8B-Instruct 27.0%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Nemo, Qwen2.5 32B Instruct and Llama-3.1-8B-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. All three 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 128,000 for Mistral Nemo and 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Mistral Nemo up to 128,000, Qwen2.5 32B Instruct up to 8,192, Llama-3.1-8B-Instruct up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Mistral Nemo accepts text; Qwen2.5 32B Instruct accepts text; Llama-3.1-8B-Instruct accepts text. They handle the same number of input types.

Are any of these open source?

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

Which is newer?

Qwen2.5 32B Instruct is the newest, released Sep 17, 2024. Llama-3.1-8B-Instruct came out Jul 23, 2024; Mistral Nemo came out Jul 1, 2024. Knowledge cutoff: Mistral Nemo Jul 2024, Qwen2.5 32B Instruct Apr 2024, Llama-3.1-8B-Instruct Dec 2023.

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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