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Comparison · 2 models · Updated Nov 2, 2026

Llama 3.3 Nemotron Super 49B v1.5 vs Voxtral Small 24B 2507

Voxtral Small 24B 2507 comes out ahead, 55 to 48 on our weighted score, and it is the cheaper option too.

  1. NVIDIA

    Llama 3.3 Nemotron Super 49B v1.5

    Released Jul 25, 2025

    48/100
    • ECI—
    • Price$0.40 / $0.40
    • Context131K
    Full specs Remove Llama 3.3 Nemotron Super 49B v1.5
  2. Our pick

    Mistral AI

    Voxtral Small 24B 2507

    Released Jul 15, 2025

    55/100
    • ECI—
    • Price$0.10 / $0.40
    • Context33K
    Full specs Remove Voxtral Small 24B 2507

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Voxtral Small 24B 2507 is our pick

Voxtral Small 24B 2507 is the better all-round choice, scoring 55/100 against Llama 3.3 Nemotron Super 49B v1.5 (48). It leads on price and inputs & features. Llama 3.3 Nemotron Super 49B v1.5 wins 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 priceVoxtral Small 24B 2507Voxtral Small 24B 2507 $0.175 · 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 · Voxtral Small 24B 2507 32,768 tokens
  • Widest inputsVoxtral Small 24B 2507Llama 3.3 Nemotron Super 49B v1.5: Text · Voxtral Small 24B 2507: Text, Audio
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightLlama 3.3 Nemotron Super 49B v1.5Voxtral Small 24B 2507
Price50%6682
Inputs & features30%3545
Context window20%250
Overall100%48/10055/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Llama 3.3 Nemotron Super 49B v1.5 vs Voxtral Small 24B 2507 specifications side by side
SpecificationLlama 3.3 Nemotron Super 49B v1.5NVIDIAVoxtral Small 24B 2507Mistral AI
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.40$0.10 (best)
Output$0.40$0.40
Cached input——
Blended (3:1)$0.40$0.175 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 1 providersOfficial Mistral API
Limits
Context window131,072 tokens (best)32,768 tokens
Max output131,072 tokens (best)32,768 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoYes
VideoNoNo
ReasoningYesNo
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenOpenApache 2.0
API model ID—voxtral-small-latest
API providers110 (best)
ReleasedJul 25, 2025Jul 15, 2025
Knowledge cutoff——
03 — Cost

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 v1.5$4.80
  • Voxtral Small 24B 2507$1.80
04 — Questions

Which should you choose?

Which is better: Llama 3.3 Nemotron Super 49B v1.5 or Voxtral Small 24B 2507?

Voxtral Small 24B 2507 is the better all-round choice, scoring 55/100 against Llama 3.3 Nemotron Super 49B v1.5 (48). It leads on price and inputs & features. Llama 3.3 Nemotron Super 49B v1.5 wins 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 v1.5 or Voxtral Small 24B 2507?

Voxtral Small 24B 2507 is cheaper at $0.10 input / $0.40 output per million tokens (official Mistral 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). At a typical mix of three input tokens to one output token, that is $0.175 per million tokens for Voxtral Small 24B 2507 versus $0.40 for Llama 3.3 Nemotron Super 49B v1.5 (2.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Llama 3.3 Nemotron Super 49B v1.5 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 v1.5 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 v1.5 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 v1.5 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 v1.5 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?

Llama 3.3 Nemotron Super 49B v1.5 is the newest, released Jul 25, 2025. Voxtral Small 24B 2507 came out Jul 15, 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 Nov 2, 2026.

05 — Keep comparing

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