Ministral 14B vs Llama-3.1-8B-Instruct
Ministral 14B comes out ahead, 64 to 56 on our weighted score, though Llama-3.1-8B-Instruct is 22% cheaper per token.
- Our pick
Mistral AIMinistral 14B
64/100- ECI—
- Price$0.20 / $0.20
- Context262K
MetaLlama-3.1-8B-Instruct
56/100- ECI116.6
- Price$0.152 / $0.167
- Context128K
Add a model
Make it a three-way comparison.
Ministral 14B is our pick
Ministral 14B is the better all-round choice, scoring 64/100 against Llama-3.1-8B-Instruct (56). It leads on inputs & features and context window. Llama-3.1-8B-Instruct wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceLlama-3.1-8B-InstructLlama-3.1-8B-Instruct $0.156 · Ministral 14B $0.20 per 1M tokens (3:1 blend)
- Longest contextMinistral 14BMinistral 14B 262,144 · Llama-3.1-8B-Instruct 128,000 tokens
- Widest inputsMinistral 14BMinistral 14B: 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 14B | Llama-3.1-8B-Instruct |
|---|---|---|---|
| Price | 50% | 83 | 88 |
| Inputs & features | 30% | 50 | 25 |
| Context window | 20% | 37 | 24 |
| Overall | 100% | 64/100 | 56/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Ministral 14BMistral AI | Llama-3.1-8B-InstructMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 116.6 |
| ECI rank | — | #145 of 148 |
| GPQA DiamondGraduate-level science questions | — | 27.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 1.7% |
| Price per million tokens | ||
| Input | $0.20 | $0.152 (best) |
| Output | $0.20 | $0.167 (best) |
| Cached input | — | — |
| Blended (3:1) | $0.20 | $0.156 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Median of 9 providers |
| Limits | ||
| Context window | 262,144 tokens (best) | 128,000 tokens |
| Max output | 262,144 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenApache-2.0 | Open |
| API model ID | — | — |
| API providers | 1 | 9 (best) |
| Released | Dec 2, 2025 | Jul 23, 2024 |
| Knowledge cutoff | — | 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 14B$2.40
- Llama-3.1-8B-Instruct$1.85
Which should you choose?
Which is better: Ministral 14B or Llama-3.1-8B-Instruct?
Ministral 14B is the better all-round choice, scoring 64/100 against Llama-3.1-8B-Instruct (56). It leads on inputs & features and context window. Llama-3.1-8B-Instruct wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Ministral 14B or Llama-3.1-8B-Instruct?
Llama-3.1-8B-Instruct is cheaper at $0.152 input / $0.167 output per million tokens (median across 9 API providers). Ministral 14B costs $0.20 input / $0.20 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.156 per million tokens for Llama-3.1-8B-Instruct versus $0.20 for Ministral 14B (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Ministral 14B has not been scored yet and Llama-3.1-8B-Instruct has an ECI of 116.6.
Which is better for coding?
There are no published SWE-bench Verified results for Ministral 14B and Llama-3.1-8B-Instruct yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
Ministral 14B has the largest context window at 262,144 tokens, against 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Ministral 14B up to 262,144, Llama-3.1-8B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Ministral 14B accepts text and images; Llama-3.1-8B-Instruct accepts text. Ministral 14B handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache-2.0), so you can self-host them.
Which is newer?
Ministral 14B is the newest, released Dec 2, 2025. Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: 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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