Mistral Small 3.2 vs Llama 3.1 Nemotron Ultra 253B
Too close to call on our weighted score (Llama 3.1 Nemotron Ultra 253B 65, Mistral Small 3.2 64). The right pick depends on what you value most.
Mistral AIMistral Small 3.2
64/100- ECI131.7
- Price$0.10 / $0.30
- Context128K
NVIDIALlama 3.1 Nemotron Ultra 253B
65/100- ECI—
- PriceFree / Free
- Context128K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 1 points (Llama 3.1 Nemotron Ultra 253B 65/100, Mistral Small 3.2 64/100), so choose by what matters most for your work: Llama 3.1 Nemotron Ultra 253B 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 Nemotron Ultra 253BLlama 3.1 Nemotron Ultra 253B Free · Mistral Small 3.2 $0.15 per 1M tokens (3:1 blend)
- Longest contextAbout the sameMistral Small 3.2 128,000 · Llama 3.1 Nemotron Ultra 253B 128,000 tokens
- Widest inputsMistral Small 3.2Mistral Small 3.2: Text, Images · Llama 3.1 Nemotron Ultra 253B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Small 3.2 | Llama 3.1 Nemotron Ultra 253B |
|---|---|---|---|
| Price | 50% | 89 | 100 |
| Inputs & features | 30% | 50 | 35 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 64/100 | 65/100 |
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 | Mistral Small 3.2Mistral AI | Llama 3.1 Nemotron Ultra 253BNVIDIA |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 131.7 | — |
| ECI rank | #123 of 148 | — |
| GPQA DiamondGraduate-level science questions | 49.1% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 30.3% | — |
| Price per million tokens | ||
| Input | $0.10 | Free (best) |
| Output | $0.30 | Free (best) |
| Cached input | — | — |
| Blended (3:1) | $0.15 | Free (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Official Nvidia API |
| Limits | ||
| Context window | 128,000 tokens | 128,000 tokens |
| Max output | 16,384 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Open |
| API model ID | mistral-small-2506 | nvidia/llama-3.1-nemotron-ultra-253b-v1 |
| API providers | 6 (best) | 1 |
| Released | Jun 20, 2025 | Apr 7, 2025 |
| Knowledge cutoff | Mar 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mistral Small 3.2$1.60
- Llama 3.1 Nemotron Ultra 253BFree
Which should you choose?
Which is better: Mistral Small 3.2 or Llama 3.1 Nemotron Ultra 253B?
It is close. Our weighted score puts them within 1 points (Llama 3.1 Nemotron Ultra 253B 65/100, Mistral Small 3.2 64/100), so choose by what matters most for your work: Llama 3.1 Nemotron Ultra 253B 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, Mistral Small 3.2 or Llama 3.1 Nemotron Ultra 253B?
Llama 3.1 Nemotron Ultra 253B is cheaper at Free input / Free output per million tokens (official Nvidia API price). Mistral Small 3.2 costs $0.10 input / $0.30 output per million tokens (official Mistral API price). Llama 3.1 Nemotron Ultra 253B is listed as free.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Mistral Small 3.2 has an ECI of 131.7 and Llama 3.1 Nemotron Ultra 253B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Small 3.2 and Llama 3.1 Nemotron Ultra 253B 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?
Mistral Small 3.2 and Llama 3.1 Nemotron Ultra 253B share the same 128,000-token context window. Maximum output per response: Mistral Small 3.2 up to 16,384, Llama 3.1 Nemotron Ultra 253B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Mistral Small 3.2 accepts text and images; Llama 3.1 Nemotron Ultra 253B accepts text. Mistral Small 3.2 handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights, so you can self-host them.
Which is newer?
Mistral Small 3.2 is the newest, released Jun 20, 2025. Llama 3.1 Nemotron Ultra 253B came out Apr 7, 2025. Knowledge cutoff: Mistral Small 3.2 Mar 2025.
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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