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Comparison · 3 models · Updated Oct 4, 2026

Llama 3.1 Nemotron 70B Instruct vs Qwen3-VL 30B-A3B vs Voxtral Small 24B 2507

Qwen3-VL 30B-A3B comes out ahead, 59 to 55 and 45 on our weighted score, though Voxtral Small 24B 2507 is 2.3× cheaper per token.

  1. NVIDIA

    Llama 3.1 Nemotron 70B Instruct

    Released Apr 15, 2025

    45/100
    • ECI—
    • Price$0.478 / $0.504
    • Context128K
    Full specs Remove Llama 3.1 Nemotron 70B Instruct
  2. Our pick

    Alibaba (Qwen)

    Qwen3-VL 30B-A3B

    Released Apr 2025

    59/100
    • ECI—
    • Price$0.20 / $0.80
    • Context131K
    Full specs Remove Qwen3-VL 30B-A3B

  3. Mistral AI

    Voxtral Small 24B 2507

    Released Jul 15, 2025

    55/100
    • ECI—
    • Price$0.10 / $0.30
    • Context33K
    Full specs Remove Voxtral Small 24B 2507
01 — Verdict

Qwen3-VL 30B-A3B is our pick

Qwen3-VL 30B-A3B is the better all-round choice, scoring 59/100 against Voxtral Small 24B 2507 (55) and Llama 3.1 Nemotron 70B Instruct (45). It leads on inputs & features. Voxtral Small 24B 2507 wins 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 priceVoxtral Small 24B 2507Voxtral Small 24B 2507 $0.15 · Qwen3-VL 30B-A3B $0.35 · Llama 3.1 Nemotron 70B Instruct $0.485 per 1M tokens (3:1 blend)
  • Longest contextQwen3-VL 30B-A3BQwen3-VL 30B-A3B 131,072 · Llama 3.1 Nemotron 70B Instruct 128,000 · Voxtral Small 24B 2507 32,768 tokens
  • Widest inputsQwen3-VL 30B-A3B and Voxtral Small 24B 2507Llama 3.1 Nemotron 70B Instruct: Text · Qwen3-VL 30B-A3B: Text, Images · 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 3.1 Nemotron 70B InstructQwen3-VL 30B-A3BVoxtral Small 24B 2507
Price50%657289
Inputs & features30%256035
Context window20%24240
Overall100%45/10059/10055/100

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 3.1 Nemotron 70B Instruct vs Qwen3-VL 30B-A3B vs Voxtral Small 24B 2507 specifications side by side
SpecificationLlama 3.1 Nemotron 70B InstructNVIDIAQwen3-VL 30B-A3BAlibaba (Qwen)Voxtral Small 24B 2507Mistral AI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.478$0.20$0.10 (best)
Output$0.504$0.80$0.30 (best)
Cached input———
Blended (3:1)$0.485$0.35$0.15 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Alibaba APIOfficial Mistral API
Limits
Context window128,000 tokens131,072 tokens (best)32,768 tokens
Max output8,192 tokens32,768 tokens (best)32,768 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoYes
VideoNoNoNo
ReasoningNoYesNo
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpenApache 2.0
API model IDnvidia/llama-3.1-nemotron-70b-instructqwen3-vl-30b-a3bvoxtral-small-latest
API providers317 (best)
ReleasedApr 15, 2025Apr 2025Jul 15, 2025
Knowledge cutoff—Apr 2025—
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 3.1 Nemotron 70B Instruct$5.79
  • Qwen3-VL 30B-A3B$3.60
  • Voxtral Small 24B 2507$1.60
04 — Questions

Which should you choose?

Which is better: Llama 3.1 Nemotron 70B Instruct, Qwen3-VL 30B-A3B or Voxtral Small 24B 2507?

Qwen3-VL 30B-A3B is the better all-round choice, scoring 59/100 against Voxtral Small 24B 2507 (55) and Llama 3.1 Nemotron 70B Instruct (45). It leads on inputs & features. Voxtral Small 24B 2507 wins 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, Llama 3.1 Nemotron 70B Instruct, Qwen3-VL 30B-A3B or Voxtral Small 24B 2507?

Voxtral Small 24B 2507 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). Qwen3-VL 30B-A3B costs $0.20 input / $0.80 output per million tokens (official Alibaba API price); Llama 3.1 Nemotron 70B Instruct costs $0.478 input / $0.504 output per million tokens (median across 2 API providers; free on Nvidia). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Voxtral Small 24B 2507 versus $0.35 for Qwen3-VL 30B-A3B (2.3× as much) and $0.485 for Llama 3.1 Nemotron 70B Instruct (3.2× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Llama 3.1 Nemotron 70B Instruct has not been scored yet, Qwen3-VL 30B-A3B 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 3.1 Nemotron 70B Instruct, Qwen3-VL 30B-A3B and Voxtral Small 24B 2507 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

Qwen3-VL 30B-A3B has the largest context window at 131,072 tokens, against 128,000 for Llama 3.1 Nemotron 70B Instruct and 32,768 for Voxtral Small 24B 2507. Maximum output per response: Llama 3.1 Nemotron 70B Instruct up to 8,192, Qwen3-VL 30B-A3B up to 32,768, Voxtral Small 24B 2507 up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Llama 3.1 Nemotron 70B Instruct accepts text; Qwen3-VL 30B-A3B accepts text and images; Voxtral Small 24B 2507 accepts text and audio. Qwen3-VL 30B-A3B handles the widest range of inputs.

Are any of these open source?

Yes, all three 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 3.1 Nemotron 70B Instruct came out Apr 15, 2025; Qwen3-VL 30B-A3B came out Apr 2025. Knowledge cutoff: Qwen3-VL 30B-A3B Apr 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.

05 — Keep comparing

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