Mistral Nemotron vs Llama 3.3 Nemotron Super 49B v1.5
Mistral Nemotron comes out ahead, 62 to 50 on our weighted score, and it is the cheaper option too.
- Our pick
NVIDIAMistral Nemotron
62/100- ECI—
- PriceFree / Free
- Context128K
- NVIDIA
Llama 3.3 Nemotron Super 49B v1.5
50/100- ECI—
- Price$0.40 / $0.40
- Context131K
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Make it a three-way comparison.
Mistral Nemotron is our pick
Mistral Nemotron is the better all-round choice, scoring 62/100 against Llama 3.3 Nemotron Super 49B v1.5 (50). It leads on price. Llama 3.3 Nemotron Super 49B v1.5 wins 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 priceMistral NemotronMistral Nemotron Free · Llama 3.3 Nemotron Super 49B v1.5 $0.40 per 1M tokens (3:1 blend)
- Longest contextLlama 3.3 Nemotron Super 49B v1.5Llama 3.3 Nemotron Super 49B v1.5 131,072 · Mistral Nemotron 128,000 tokens
- Widest inputsSame inputsMistral Nemotron: Text · Llama 3.3 Nemotron Super 49B v1.5: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Nemotron | Llama 3.3 Nemotron Super 49B v1.5 |
|---|---|---|---|
| Price | 50% | 100 | 69 |
| Inputs & features | 30% | 25 | 35 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 62/100 | 50/100 |
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 NemotronNVIDIA | Llama 3.3 Nemotron Super 49B v1.5NVIDIA |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | Free (best) | $0.40 |
| Output | Free (best) | $0.40 |
| Cached input | — | — |
| Blended (3:1) | Free (best) | $0.40 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Nvidia API | Median of 1 providers |
| Limits | ||
| Context window | 128,000 tokens | 131,072 tokens (best) |
| Max output | 8,192 tokens | 131,072 tokens (best) |
| 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-3.3-nemotron-super-49b-v1.5 |
| API providers | 1 | 2 (best) |
| Released | Jun 11, 2025 | Jul 25, 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 3.3 Nemotron Super 49B v1.5$4.80
Which should you choose?
Which is better: Mistral Nemotron or Llama 3.3 Nemotron Super 49B v1.5?
Mistral Nemotron is the better all-round choice, scoring 62/100 against Llama 3.3 Nemotron Super 49B v1.5 (50). It leads on price. Llama 3.3 Nemotron Super 49B v1.5 wins 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 3.3 Nemotron Super 49B v1.5?
Mistral Nemotron is cheaper at Free input / Free output per million tokens (official Nvidia API price). Llama 3.3 Nemotron Super 49B v1.5 costs $0.40 input / $0.40 output per million tokens (median across 1 API provider; free on Nvidia). Mistral Nemotron is listed as free.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Mistral Nemotron has not been scored yet and Llama 3.3 Nemotron Super 49B v1.5 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Nemotron and Llama 3.3 Nemotron Super 49B v1.5 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?
Llama 3.3 Nemotron Super 49B v1.5 has the largest context window at 131,072 tokens, against 128,000 for Mistral Nemotron. Maximum output per response: Mistral Nemotron up to 8,192, Llama 3.3 Nemotron Super 49B v1.5 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Mistral Nemotron accepts text; Llama 3.3 Nemotron Super 49B v1.5 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 3.3 Nemotron Super 49B v1.5 is the newest, released Jul 25, 2025. Mistral Nemotron came out Jun 11, 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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