Ministral 8B Instruct vs Gemma 3 4B IT vs Llama-3.1-8B-Instruct
Gemma 3 4B IT comes out ahead, 47 to 42 and 42 on our weighted score, and it is the cheaper option too.
Mistral AIMinistral 8B Instruct
42/100- ECI—
- Price$0.15 / $0.15
- Context131K
- Our pick
GoogleGemma 3 4B IT
47/100- ECI116.1
- Price$0.05 / $0.10
- Context131K
MetaLlama-3.1-8B-Instruct
42/100- ECI116.6
- Price$0.152 / $0.167
- Context128K
Gemma 3 4B IT is our pick
Gemma 3 4B IT is the better all-round choice, scoring 47/100 against Ministral 8B Instruct (42) and Llama-3.1-8B-Instruct (42). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because Ministral 8B Instruct has no Capabilities Index score yet.
- CapabilityMinistral 8B InstructShared benchmarks: Ministral 8B Instruct 27.2% · Llama-3.1-8B-Instruct 27.0% · Gemma 3 4B IT 23.2%
- Lowest priceGemma 3 4B ITGemma 3 4B IT $0.063 · Ministral 8B Instruct $0.15 · Llama-3.1-8B-Instruct $0.156 per 1M tokens (3:1 blend)
- Longest contextMinistral 8B Instruct and Gemma 3 4B ITMinistral 8B Instruct 131,072 · Gemma 3 4B IT 131,072 · Llama-3.1-8B-Instruct 128,000 tokens
- Widest inputsGemma 3 4B ITMinistral 8B Instruct: Text · Gemma 3 4B IT: Text, Images · Llama-3.1-8B-Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Ministral 8B Instruct | Gemma 3 4B IT | Llama-3.1-8B-Instruct |
|---|---|---|---|---|
| CapabilityShared benchmarks | 50% | 27 | 23 | 27 |
| Price | 25% | 89 | 100 | 88 |
| Inputs & features | 15% | 25 | 50 | 25 |
| Context window | 10% | 24 | 24 | 24 |
| Overall | 100% | 42/100 | 47/100 | 42/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Ministral 8B InstructMistral AI | Gemma 3 4B ITGoogle | Llama-3.1-8B-InstructMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 116.1 | 116.6 (best) |
| ECI rank | — | #146 of 148 | #145 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 27.2% (best) | 23.2% | 27.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 7.5% (best) | 1.7% |
| Price per million tokens | |||
| Input | $0.15 | $0.05 (best) | $0.152 |
| Output | $0.15 | $0.10 (best) | $0.167 |
| Cached input | — | — | — |
| Blended (3:1) | $0.15 | $0.063 (best) | $0.156 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 7 providers | Median of 9 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 131,072 tokens (best) | 128,000 tokens |
| Max output | 8,192 tokens | 131,072 tokens (best) | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | 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 | OpenMistral Research License | Open | Open |
| API model ID | — | — | — |
| API providers | 1 | 7 | 9 (best) |
| Released | Oct 16, 2024 | Mar 12, 2025 | Jul 23, 2024 |
| Knowledge cutoff | — | Aug 2024 | Dec 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Ministral 8B Instruct$1.80
- Gemma 3 4B IT$0.70
- Llama-3.1-8B-Instruct$1.85
Which should you choose?
Which is better: Ministral 8B Instruct, Gemma 3 4B IT or Llama-3.1-8B-Instruct?
Gemma 3 4B IT is the better all-round choice, scoring 47/100 against Ministral 8B Instruct (42) and Llama-3.1-8B-Instruct (42). It leads on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond), because Ministral 8B Instruct has no Capabilities Index score yet.
Which is cheaper, Ministral 8B Instruct, Gemma 3 4B IT or Llama-3.1-8B-Instruct?
Gemma 3 4B IT is cheaper at $0.05 input / $0.10 output per million tokens (median across 7 API providers). Ministral 8B Instruct costs $0.15 input / $0.15 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 $0.063 per million tokens for Gemma 3 4B IT versus $0.15 for Ministral 8B Instruct (2.4× as much) and $0.156 for Llama-3.1-8B-Instruct (2.5× as much).
Which scores higher on benchmarks?
Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond): Ministral 8B Instruct 27.2%, Llama-3.1-8B-Instruct 27.0% and Gemma 3 4B IT 23.2%. On individual benchmarks: GPQA Diamond — Ministral 8B Instruct 27.2%, Llama-3.1-8B-Instruct 27.0%, Gemma 3 4B IT 23.2%.
Which is better for coding?
There are no published SWE-bench Verified results for Ministral 8B Instruct, Gemma 3 4B IT and Llama-3.1-8B-Instruct yet, so there is no like-for-like coding score. On overall capability, Ministral 8B 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?
Ministral 8B Instruct and Gemma 3 4B IT have the largest context windows (131,072 and 131,072 tokens), against 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Ministral 8B Instruct up to 8,192, Gemma 3 4B IT up to 131,072, Llama-3.1-8B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Ministral 8B Instruct accepts text; Gemma 3 4B IT accepts text and images; Llama-3.1-8B-Instruct accepts text. Gemma 3 4B IT handles the widest range of inputs.
Are any of these open source?
Yes, all three publish their weights (Mistral Research License), so you can self-host them.
Which is newer?
Gemma 3 4B IT is the newest, released Mar 12, 2025. Ministral 8B Instruct came out Oct 16, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Gemma 3 4B 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.
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