ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Llama-3.1-8B-Instruct vs Ministral 3B vs Qwen2.5 7B Instruct

Ministral 3B comes out ahead, 49 to 46 and 44 on our weighted score, and it is the cheaper option too.

  1. 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
  2. Our pick

    Mistral AI

    Ministral 3B

    Released Oct 16, 2024

    49/100
    • ECI118.1
    • Price$0.10 / $0.10
    • Context128K
    Full specs Remove Ministral 3B

  3. Alibaba (Qwen)

    Qwen2.5 7B Instruct

    Released Sep 19, 2024

    44/100
    • ECI118.5
    • Price$0.175 / $0.70
    • Context131K
    Full specs Remove Qwen2.5 7B Instruct
01 — Verdict

Ministral 3B is our pick

Ministral 3B is the better all-round choice, scoring 49/100 against Llama-3.1-8B-Instruct (46) and Qwen2.5 7B Instruct (44). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen2.5 7B InstructCapabilities Index (ECI): Qwen2.5 7B Instruct 118.5 · Ministral 3B 118.1 · Llama-3.1-8B-Instruct 116.6
  • Lowest priceMinistral 3BMinistral 3B $0.10 · Llama-3.1-8B-Instruct $0.156 · Qwen2.5 7B Instruct $0.306 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 7B InstructQwen2.5 7B Instruct 131,072 · Llama-3.1-8B-Instruct 128,000 · Ministral 3B 128,000 tokens
  • Widest inputsSame inputsLlama-3.1-8B-Instruct: Text · Ministral 3B: Text · Qwen2.5 7B Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightLlama-3.1-8B-InstructMinistral 3BQwen2.5 7B Instruct
CapabilityCapabilities Index (ECI)50%363838
Price25%889774
Inputs & features15%252525
Context window10%242424
Overall100%46/10049/10044/100
02 — Side by side

Every spec in one table

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

Llama-3.1-8B-Instruct vs Ministral 3B vs Qwen2.5 7B Instruct specifications side by side
SpecificationLlama-3.1-8B-InstructMetaMinistral 3BMistral AIQwen2.5 7B InstructAlibaba (Qwen)
Capability
Capabilities Index (ECI)116.6118.1118.5 (best)
ECI rank#145 of 148#144 of 148#141 of 148 (best)
GPQA DiamondGraduate-level science questions27.0%25.3%35.5% (best)
OTIS Mock AIME 2024–2025Competition mathematics1.7%—2.5% (best)
Price per million tokens
Input$0.152$0.10 (best)$0.175
Output$0.167$0.10 (best)$0.70
Cached input———
Blended (3:1)$0.156$0.10 (best)$0.306
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 9 providersMedian of 1 providersOfficial Alibaba API
Limits
Context window128,000 tokens128,000 tokens131,072 tokens (best)
Max output4,096 tokens8,192 tokens (best)8,192 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model ID——qwen2-5-7b-instruct
API providers9 (best)11
ReleasedJul 23, 2024Oct 16, 2024Sep 19, 2024
Knowledge cutoffDec 2023Mar 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.

  • Llama-3.1-8B-Instruct$1.85
  • Ministral 3B$1.20
  • Qwen2.5 7B Instruct$3.15
04 — Questions

Which should you choose?

Which is better: Llama-3.1-8B-Instruct, Ministral 3B or Qwen2.5 7B Instruct?

Ministral 3B is the better all-round choice, scoring 49/100 against Llama-3.1-8B-Instruct (46) and Qwen2.5 7B Instruct (44). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Llama-3.1-8B-Instruct, Ministral 3B or Qwen2.5 7B Instruct?

Ministral 3B is cheaper at $0.10 input / $0.10 output per million tokens (median across 1 API provider). Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 API providers); Qwen2.5 7B Instruct costs $0.175 input / $0.70 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.10 per million tokens for Ministral 3B versus $0.156 for Llama-3.1-8B-Instruct (1.6× as much) and $0.306 for Qwen2.5 7B Instruct (3.1× as much).

Which scores higher on benchmarks?

Qwen2.5 7B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 7B Instruct 118.5 (#141 of 148), Ministral 3B 118.1 (#144 of 148) and Llama-3.1-8B-Instruct 116.6 (#145 of 148). The confidence ranges of the top two overlap (110.7–121.3 vs 107.4–121.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen2.5 7B Instruct 35.5%, Llama-3.1-8B-Instruct 27.0%, Ministral 3B 25.3%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.1-8B-Instruct, Ministral 3B and Qwen2.5 7B Instruct yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 7B 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 7B Instruct has the largest context window at 131,072 tokens, against 128,000 for Llama-3.1-8B-Instruct and 128,000 for Ministral 3B. Maximum output per response: Llama-3.1-8B-Instruct up to 4,096, Ministral 3B up to 8,192, Qwen2.5 7B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Llama-3.1-8B-Instruct accepts text; Ministral 3B accepts text; Qwen2.5 7B 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?

Ministral 3B is the newest, released Oct 16, 2024. Qwen2.5 7B Instruct came out Sep 19, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.1-8B-Instruct Dec 2023, Ministral 3B Mar 2024, Qwen2.5 7B 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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