Llama 3.3 Nemotron Super 49B v1 vs Voxtral Small 24B 2507
Llama 3.3 Nemotron Super 49B v1 comes out ahead, 60 to 55 on our weighted score.
- Our pick
NVIDIALlama 3.3 Nemotron Super 49B v1
60/100- ECI—
- Price$0.15 / $0.15
- Context131K
Mistral AIVoxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.30
- Context33K
Add a model
Make it a three-way comparison.
Llama 3.3 Nemotron Super 49B v1 is our pick
Llama 3.3 Nemotron Super 49B v1 is the better all-round choice, scoring 60/100 against Voxtral Small 24B 2507 (55). It leads on context window. 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 priceLlama 3.3 Nemotron Super 49B v1 $0.15 · Voxtral Small 24B 2507 $0.15 per 1M tokens (3:1 blend)
- Longest contextLlama 3.3 Nemotron Super 49B v1Llama 3.3 Nemotron Super 49B v1 131,072 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsVoxtral Small 24B 2507Llama 3.3 Nemotron Super 49B v1: Text · Voxtral Small 24B 2507: Text, Audio
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Llama 3.3 Nemotron Super 49B v1 | Voxtral Small 24B 2507 |
|---|---|---|---|
| Price | 50% | 89 | 89 |
| Inputs & features | 30% | 35 | 35 |
| Context window | 20% | 24 | 0 |
| Overall | 100% | 60/100 | 55/100 |
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 | Llama 3.3 Nemotron Super 49B v1NVIDIA | Voxtral Small 24B 2507Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.15 | $0.10 (best) |
| Output | $0.15 (best) | $0.30 |
| Cached input | — | — |
| Blended (3:1) | $0.15 | $0.15 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Mistral API |
| Limits | ||
| Context window | 131,072 tokens (best) | 32,768 tokens |
| Max output | 131,072 tokens (best) | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | Yes |
| Video | No | No |
| Reasoning | Yes | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | OpenApache 2.0 |
| API model ID | nvidia/llama-3.3-nemotron-super-49b-v1 | voxtral-small-latest |
| API providers | 2 | 7 (best) |
| Released | Apr 7, 2025 | Jul 15, 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.
- Llama 3.3 Nemotron Super 49B v1$1.80
- Voxtral Small 24B 2507$1.60
Which should you choose?
Which is better: Llama 3.3 Nemotron Super 49B v1 or Voxtral Small 24B 2507?
Llama 3.3 Nemotron Super 49B v1 is the better all-round choice, scoring 60/100 against Voxtral Small 24B 2507 (55). It leads on context window. 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, Llama 3.3 Nemotron Super 49B v1 or Voxtral Small 24B 2507?
Llama 3.3 Nemotron Super 49B v1 and Voxtral Small 24B 2507 cost the same: $0.15 input / $0.15 output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Llama 3.3 Nemotron Super 49B v1 has not been scored yet and Voxtral Small 24B 2507 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Llama 3.3 Nemotron Super 49B v1 and Voxtral Small 24B 2507 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 has the largest context window at 131,072 tokens, against 32,768 for Voxtral Small 24B 2507. Maximum output per response: Llama 3.3 Nemotron Super 49B v1 up to 131,072, Voxtral Small 24B 2507 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Llama 3.3 Nemotron Super 49B v1 accepts text; Voxtral Small 24B 2507 accepts text and audio. Voxtral Small 24B 2507 handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Voxtral Small 24B 2507 is the newest, released Jul 15, 2025. Llama 3.3 Nemotron Super 49B v1 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.
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