Ministral 8B Instruct vs Nova Micro vs Llama-3.1-8B-Instruct
Nova Micro comes out ahead, 62 to 57 and 56 on our weighted score, and it is the cheaper option too.
Mistral AIMinistral 8B Instruct
57/100- ECI—
- Price$0.15 / $0.15
- Context131K
- Our pick
AmazonNova Micro
62/100- ECI—
- Price$0.035 / $0.14
- Context128K
MetaLlama-3.1-8B-Instruct
56/100- ECI116.6
- Price$0.152 / $0.167
- Context128K
Nova Micro is our pick
Nova Micro is the better all-round choice, scoring 62/100 against Ministral 8B Instruct (57) and Llama-3.1-8B-Instruct (56). It leads 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 priceNova MicroNova Micro $0.061 · Ministral 8B Instruct $0.15 · Llama-3.1-8B-Instruct $0.156 per 1M tokens (3:1 blend)
- Longest contextMinistral 8B InstructMinistral 8B Instruct 131,072 · Nova Micro 128,000 · Llama-3.1-8B-Instruct 128,000 tokens
- Widest inputsSame inputsMinistral 8B Instruct: Text · Nova Micro: Text · Llama-3.1-8B-Instruct: Text
- Self-hostingMinistral 8B Instruct and Llama-3.1-8B-InstructPublishes downloadable weights (Mistral Research License)
| Measure | Weight | Ministral 8B Instruct | Nova Micro | Llama-3.1-8B-Instruct |
|---|---|---|---|---|
| Price | 50% | 89 | 100 | 88 |
| Inputs & features | 30% | 25 | 25 | 25 |
| Context window | 20% | 24 | 24 | 24 |
| Overall | 100% | 57/100 | 62/100 | 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 8B InstructMistral AI | Nova MicroAmazon | Llama-3.1-8B-InstructMeta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | 116.6 |
| ECI rank | — | — | #145 of 148 |
| GPQA DiamondGraduate-level science questions | 27.2% (best) | — | 27.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 1.7% |
| Price per million tokens | |||
| Input | $0.15 | $0.035 (best) | $0.152 |
| Output | $0.15 | $0.14 (best) | $0.167 |
| Cached input | — | $0.0088 | — |
| Blended (3:1) | $0.15 | $0.061 (best) | $0.156 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Amazon Bedrock API | Median of 9 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 8,192 tokens | 10,000 tokens (best) | 4,096 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | 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 | OpenMistral Research License | Proprietary | Open |
| API model ID | — | amazon.nova-micro-v1:0 | — |
| API providers | 1 | 3 | 9 (best) |
| Released | Oct 16, 2024 | Dec 3, 2024 | Jul 23, 2024 |
| Knowledge cutoff | — | Oct 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
- Nova Micro$0.63
- Llama-3.1-8B-Instruct$1.85
Which should you choose?
Which is better: Ministral 8B Instruct, Nova Micro or Llama-3.1-8B-Instruct?
Nova Micro is the better all-round choice, scoring 62/100 against Ministral 8B Instruct (57) and Llama-3.1-8B-Instruct (56). It leads 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 8B Instruct, Nova Micro or Llama-3.1-8B-Instruct?
Nova Micro is cheaper at $0.035 input / $0.14 output per million tokens (official Amazon Bedrock API price). 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 $0.061 per million tokens for Nova Micro 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?
There is no independent benchmark that covers all three models yet. Ministral 8B Instruct has not been scored yet, Nova Micro 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 8B Instruct, Nova Micro 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. All three support tool calling for agent workflows.
Which has the bigger context window?
Ministral 8B Instruct has the largest context window at 131,072 tokens, against 128,000 for Nova Micro and 128,000 for Llama-3.1-8B-Instruct. Maximum output per response: Ministral 8B Instruct up to 8,192, Nova Micro up to 10,000, Llama-3.1-8B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Ministral 8B Instruct accepts text; Nova Micro accepts text; Llama-3.1-8B-Instruct accepts text. They handle the same number of input types.
Are any of these open source?
Ministral 8B Instruct and Llama-3.1-8B-Instruct publishes its weights (Mistral Research License) and can be self-hosted; Nova Micro is proprietary.
Which is newer?
Nova Micro is the newest, released Dec 3, 2024. Ministral 8B Instruct came out Oct 16, 2024; Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Nova Micro Oct 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.
