Mistral Nemo vs Llama-3.1-8B-Instruct
Too close to call on our weighted score (Mistral Nemo 48, Llama-3.1-8B-Instruct 46). The right pick depends on what you value most.
Mistral AIMistral Nemo
48/100- ECI118.7
- Price$0.15 / $0.15
- Context128K
MetaLlama-3.1-8B-Instruct
46/100- ECI116.6
- Price$0.152 / $0.167
- Context128K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 2 points (Mistral Nemo 48/100, Llama-3.1-8B-Instruct 46/100), so choose by what matters most for your work: Mistral Nemo for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMistral NemoCapabilities Index (ECI): Mistral Nemo 118.7 · Llama-3.1-8B-Instruct 116.6
- Lowest priceMistral NemoMistral Nemo $0.15 · Llama-3.1-8B-Instruct $0.156 per 1M tokens (3:1 blend)
- Longest contextAbout the sameMistral Nemo 128,000 · Llama-3.1-8B-Instruct 128,000 tokens
- Widest inputsSame inputsMistral Nemo: Text · Llama-3.1-8B-Instruct: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Nemo | Llama-3.1-8B-Instruct |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 39 | 36 |
| Price | 25% | 89 | 88 |
| Inputs & features | 15% | 25 | 25 |
| Context window | 10% | 24 | 24 |
| Overall | 100% | 48/100 | 46/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral NemoMistral AI | Llama-3.1-8B-InstructMeta |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 118.7 (best) | 116.6 |
| ECI rank | #140 of 148 (best) | #145 of 148 |
| GPQA DiamondGraduate-level science questions | 29.9% (best) | 27.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 1.7% |
| Price per million tokens | ||
| Input | $0.15 (best) | $0.152 |
| Output | $0.15 (best) | $0.167 |
| Cached input | — | — |
| Blended (3:1) | $0.15 (best) | $0.156 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 9 providers |
| Limits | ||
| Context window | 128,000 tokens | 128,000 tokens |
| Max output | 128,000 tokens (best) | 4,096 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | mistral-nemo | — |
| API providers | 5 | 9 (best) |
| Released | Jul 1, 2024 | Jul 23, 2024 |
| Knowledge cutoff | Jul 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.
- Mistral Nemo$1.80
- Llama-3.1-8B-Instruct$1.85
Which should you choose?
Which is better: Mistral Nemo or Llama-3.1-8B-Instruct?
It is close. Our weighted score puts them within 2 points (Mistral Nemo 48/100, Llama-3.1-8B-Instruct 46/100), so choose by what matters most for your work: Mistral Nemo for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Nemo or Llama-3.1-8B-Instruct?
Mistral Nemo is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). 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 $0.15 per million tokens for Mistral Nemo versus $0.156 for Llama-3.1-8B-Instruct (1× as much).
Which scores higher on benchmarks?
Mistral Nemo scores higher on the Capabilities Index (ECI): Mistral Nemo 118.7 (#140 of 148) and Llama-3.1-8B-Instruct 116.6 (#145 of 148). The confidence ranges of the top two overlap (111.3–121.5 vs 106.3–121.6), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Nemo 29.9%, Llama-3.1-8B-Instruct 27.0%.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Nemo and Llama-3.1-8B-Instruct yet, so there is no like-for-like coding score. On overall capability, Mistral Nemo leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Mistral Nemo and Llama-3.1-8B-Instruct share the same 128,000-token context window. Maximum output per response: Mistral Nemo up to 128,000, Llama-3.1-8B-Instruct up to 4,096 tokens.
Which can read images, PDFs, audio or video?
Mistral Nemo accepts text; Llama-3.1-8B-Instruct accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Llama-3.1-8B-Instruct is the newest, released Jul 23, 2024. Mistral Nemo came out Jul 1, 2024. Knowledge cutoff: Mistral Nemo Jul 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.
Related comparisons
- Add Qwen2.5 7B InstructThree-way comparison
- Mistral Nemo vs Qwen2.5 7B InstructAlibaba (Qwen) · ECI 118.5
- Mistral Nemo vs Claude Haiku 3Anthropic · ECI 118.4
- Mistral Nemo vs GPT-4o miniOpenAI · ECI 126.6
- Llama-3.1-8B-Instruct vs Ministral 8B InstructMistral AI
- Llama-3.1-8B-Instruct vs Qwen2.5 7B InstructAlibaba (Qwen) · ECI 118.5
- Llama-3.1-8B-Instruct vs Gemma 3 4B ITGoogle · ECI 116.1
