Gemma 3 12B IT vs Llama-3.1-8B-Instruct vs Ministral 3B
Gemma 3 12B IT comes out ahead, 57 to 49 and 46 on our weighted score, and it is the cheaper option too.
- Our pick
GoogleGemma 3 12B IT
57/100- ECI123.5
- Price$0.05 / $0.15
- Context131K
MetaLlama-3.1-8B-Instruct
46/100- ECI116.6
- Price$0.152 / $0.167
- Context128K
Mistral AIMinistral 3B
49/100- ECI118.1
- Price$0.10 / $0.10
- Context128K
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 · Llama-3.1-8B-Instruct 128,000 · Ministral 3B 128,000 tokens
- Widest inputsGemma 3 12B ITGemma 3 12B IT: Text, Images · Llama-3.1-8B-Instruct: Text · Ministral 3B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Gemma 3 12B IT | Llama-3.1-8B-Instruct | Ministral 3B |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 45 | 36 | 38 |
| Price | 25% | 100 | 88 | 97 |
| Inputs & features | 15% | 50 | 25 | 25 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 57/100 | 46/100 | 49/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemma 3 12B ITGoogle | Llama-3.1-8B-InstructMeta | Ministral 3BMistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 123.5 (best) | 116.6 | 118.1 |
| ECI rank | #138 of 148 (best) | #145 of 148 | #144 of 148 |
| GPQA DiamondGraduate-level science questions | 39.5% (best) | 27.0% | 25.3% |
| OTIS Mock AIME 2024–2025Competition mathematics | 16.7% (best) | 1.7% | — |
| Price per million tokens | |||
| Input | $0.05 (best) | $0.152 | $0.10 |
| Output | $0.15 | $0.167 | $0.10 (best) |
| Cached input | — | — | — |
| Blended (3:1) | $0.075 (best) | $0.156 | $0.10 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 7 providers | Median of 9 providers | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 131,072 tokens (best) | 4,096 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Open |
| API model ID | — | — | — |
| API providers | 7 | 9 (best) | 1 |
| Released | Mar 12, 2025 | Jul 23, 2024 | Oct 16, 2024 |
| Knowledge cutoff | Aug 2024 | Dec 2023 | Mar 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemma 3 12B IT$0.80
- Llama-3.1-8B-Instruct$1.85
- Ministral 3B$1.20
Which should you choose?
Which is better: Gemma 3 12B IT, Llama-3.1-8B-Instruct or Ministral 3B?
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, Gemma 3 12B IT, Llama-3.1-8B-Instruct or Ministral 3B?
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 Gemma 3 12B IT, Llama-3.1-8B-Instruct and Ministral 3B 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 Llama-3.1-8B-Instruct and 128,000 for Ministral 3B. Maximum output per response: Gemma 3 12B IT up to 131,072, Llama-3.1-8B-Instruct up to 4,096, Ministral 3B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Gemma 3 12B IT accepts text and images; Llama-3.1-8B-Instruct accepts text; Ministral 3B 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: Gemma 3 12B IT Aug 2024, Llama-3.1-8B-Instruct Dec 2023, Ministral 3B Mar 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.
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