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Comparison · 3 models · Updated Oct 4, 2026

Ministral 3B vs Gemma 3 12B IT vs Llama-3.1-8B-Instruct

Gemma 3 12B IT comes out ahead, 57 to 49 and 46 on our weighted score, and it is the cheaper option too.

  1. Mistral AI

    Ministral 3B

    Released Oct 16, 2024

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

    Google

    Gemma 3 12B IT

    Released Mar 12, 2025

    57/100
    • ECI123.5
    • Price$0.05 / $0.15
    • Context131K
    Full specs Remove Gemma 3 12B IT

  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

Gemma 3 12B IT is our pick

Gemma 3 12B IT is the better all-round choice, scoring 57/100 against Ministral 3B (49) and Llama-3.1-8B-Instruct (46). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGemma 3 12B ITCapabilities Index (ECI): Gemma 3 12B IT 123.5 · Ministral 3B 118.1 · Llama-3.1-8B-Instruct 116.6
  • Lowest priceGemma 3 12B ITGemma 3 12B IT $0.075 · Ministral 3B $0.10 · Llama-3.1-8B-Instruct $0.156 per 1M tokens (3:1 blend)
  • Longest contextGemma 3 12B ITGemma 3 12B IT 131,072 · Ministral 3B 128,000 · Llama-3.1-8B-Instruct 128,000 tokens
  • Widest inputsGemma 3 12B ITMinistral 3B: Text · Gemma 3 12B IT: Text, Images · 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
MeasureWeightMinistral 3BGemma 3 12B ITLlama-3.1-8B-Instruct
CapabilityCapabilities Index (ECI)50%384536
Price25%9710088
Inputs & features15%255025
Context window10%242424
Overall100%49/10057/10046/100
02 — Side by side

Every spec in one table

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

Ministral 3B vs Gemma 3 12B IT vs Llama-3.1-8B-Instruct specifications side by side
SpecificationMinistral 3BMistral AIGemma 3 12B ITGoogleLlama-3.1-8B-InstructMeta
Capability
Capabilities Index (ECI)118.1123.5 (best)116.6
ECI rank#144 of 148#138 of 148 (best)#145 of 148
GPQA DiamondGraduate-level science questions25.3%39.5% (best)27.0%
OTIS Mock AIME 2024–2025Competition mathematics—16.7% (best)1.7%
Price per million tokens
Input$0.10$0.05 (best)$0.152
Output$0.10 (best)$0.15$0.167
Cached input———
Blended (3:1)$0.10$0.075 (best)$0.156
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 1 providersMedian of 7 providersMedian of 9 providers
Limits
Context window128,000 tokens131,072 tokens (best)128,000 tokens
Max output8,192 tokens131,072 tokens (best)4,096 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model ID———
API providers179 (best)
ReleasedOct 16, 2024Mar 12, 2025Jul 23, 2024
Knowledge cutoffMar 2024Aug 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.

  • Ministral 3B$1.20
  • Gemma 3 12B IT$0.80
  • Llama-3.1-8B-Instruct$1.85
04 — Questions

Which should you choose?

Which is better: Ministral 3B, Gemma 3 12B IT or Llama-3.1-8B-Instruct?

Gemma 3 12B IT is the better all-round choice, scoring 57/100 against Ministral 3B (49) and Llama-3.1-8B-Instruct (46). It leads on capability, price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Ministral 3B, Gemma 3 12B IT or Llama-3.1-8B-Instruct?

Gemma 3 12B IT is cheaper at $0.05 input / $0.15 output per million tokens (median across 7 API providers). Ministral 3B costs $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). At a typical mix of three input tokens to one output token, that is $0.075 per million tokens for Gemma 3 12B IT versus $0.10 for Ministral 3B (1.3× as much) and $0.156 for Llama-3.1-8B-Instruct (2.1× as much).

Which scores higher on benchmarks?

Gemma 3 12B IT scores higher on the Capabilities Index (ECI): Gemma 3 12B IT 123.5 (#138 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 (115.6–129.3 vs 107.4–121.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Gemma 3 12B IT 39.5%, 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 Ministral 3B, Gemma 3 12B IT and Llama-3.1-8B-Instruct yet, so there is no like-for-like coding score. On overall capability, Gemma 3 12B IT 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?

Gemma 3 12B IT has the largest context window at 131,072 tokens, against 128,000 for Ministral 3B and 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Ministral 3B up to 8,192, Gemma 3 12B IT up to 131,072, Llama-3.1-8B-Instruct up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Ministral 3B accepts text; Gemma 3 12B IT accepts text and images; Llama-3.1-8B-Instruct accepts text. Gemma 3 12B IT handles the widest range of inputs.

Are any of these open source?

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

Which is newer?

Gemma 3 12B IT is the newest, released Mar 12, 2025. Ministral 3B came out Oct 16, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Ministral 3B Mar 2024, Gemma 3 12B IT Aug 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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