Mistral Nemotron vs Llama 3.1 Nemotron Ultra 253B
Llama 3.1 Nemotron Ultra 253B comes out ahead, 65 to 62 on our weighted score.
NVIDIA
Mistral Nemotron
62/100- ECI—
- PriceFree / Free
- Context128K
- Our pick
NVIDIA
Llama 3.1 Nemotron Ultra 253B
65/100- ECI—
- PriceFree / Free
- Context128K
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Make it a three-way comparison.
Llama 3.1 Nemotron Ultra 253B is our pick
Llama 3.1 Nemotron Ultra 253B is the better all-round choice, scoring 65/100 against Mistral Nemotron (62). It leads on inputs & features. 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 priceSame priceMistral Nemotron Free · Llama 3.1 Nemotron Ultra 253B Free per 1M tokens (3:1 blend)
- Longest contextAbout the sameMistral Nemotron 128,000 · Llama 3.1 Nemotron Ultra 253B 128,000 tokens
- Widest inputsSame inputsMistral Nemotron: Text · 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 Nemotron | Llama 3.1 Nemotron Ultra 253B |
|---|---|---|---|
| Price | 50% | 100 | 100 |
| Inputs & features | 30% | 25 | 35 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 62/100 | 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 | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | Free | Free |
| Output | Free | Free |
| Cached input | — | — |
| Blended (3:1) | Free | Free |
| Long-context rate | Same rate | Same rate |
| Price source | Official Nvidia API | Official Nvidia API |
| Limits | ||
| Context window | 128,000 tokens | 128,000 tokens |
| Max output | 8,192 tokens | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | 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 | mistralai/mistral-nemotron | nvidia/llama-3.1-nemotron-ultra-253b-v1 |
| API providers | 1 | 1 |
| Released | Jun 11, 2025 | Apr 7, 2025 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Mistral NemotronFree
Llama 3.1 Nemotron Ultra 253BFree
Which should you choose?
Which is better: Mistral Nemotron or Llama 3.1 Nemotron Ultra 253B?
Llama 3.1 Nemotron Ultra 253B is the better all-round choice, scoring 65/100 against Mistral Nemotron (62). It leads on inputs & features. 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 Nemotron or Llama 3.1 Nemotron Ultra 253B?
Mistral Nemotron and Llama 3.1 Nemotron Ultra 253B cost the same: Free input / Free output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Mistral Nemotron has not been scored yet 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 Nemotron 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 Nemotron and Llama 3.1 Nemotron Ultra 253B share the same 128,000-token context window. Maximum output per response: Mistral Nemotron up to 8,192, Llama 3.1 Nemotron Ultra 253B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Mistral Nemotron accepts text; Llama 3.1 Nemotron Ultra 253B 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?
Mistral Nemotron is the newest, released Jun 11, 2025. Llama 3.1 Nemotron Ultra 253B came out Apr 7, 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.