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Comparison · 3 models · Updated Oct 4, 2026

Llama 3.1 Nemotron 70B Instruct vs Mistral Nemotron vs Qwen3-VL 30B-A3B

Mistral Nemotron comes out ahead, 62 to 59 and 45 on our weighted score, and it is the cheaper option too.

  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

    NVIDIA

    Mistral Nemotron

    Released Jun 11, 2025Deprecated

    62/100
    • ECI—
    • PriceFree / Free
    • Context128K
    Full specs Remove Mistral Nemotron

  3. 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
01 — Verdict

Mistral Nemotron is our pick

Mistral Nemotron is the better all-round choice, scoring 62/100 against Qwen3-VL 30B-A3B (59) and Llama 3.1 Nemotron 70B Instruct (45). It leads on price. Qwen3-VL 30B-A3B 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 · 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 · Mistral Nemotron 128,000 tokens
  • Widest inputsQwen3-VL 30B-A3BLlama 3.1 Nemotron 70B Instruct: Text · Mistral Nemotron: Text · Qwen3-VL 30B-A3B: Text, Images
  • 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 InstructMistral NemotronQwen3-VL 30B-A3B
Price50%6510072
Inputs & features30%252560
Context window20%242424
Overall100%45/10062/10059/100

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 Mistral Nemotron vs Qwen3-VL 30B-A3B specifications side by side
SpecificationLlama 3.1 Nemotron 70B InstructNVIDIAMistral NemotronNVIDIAQwen3-VL 30B-A3BAlibaba (Qwen)
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.478Free (best)$0.20
Output$0.504Free (best)$0.80
Cached input———
Blended (3:1)$0.485Free (best)$0.35
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Nvidia APIOfficial Alibaba API
Limits
Context window128,000 tokens128,000 tokens131,072 tokens (best)
Max output8,192 tokens8,192 tokens32,768 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model IDnvidia/llama-3.1-nemotron-70b-instructmistralai/mistral-nemotronqwen3-vl-30b-a3b
API providers3 (best)11
ReleasedApr 15, 2025Jun 11, 2025Apr 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
  • Mistral NemotronFree
  • Qwen3-VL 30B-A3B$3.60
04 — Questions

Which should you choose?

Which is better: Llama 3.1 Nemotron 70B Instruct, Mistral Nemotron or Qwen3-VL 30B-A3B?

Mistral Nemotron is the better all-round choice, scoring 62/100 against Qwen3-VL 30B-A3B (59) and Llama 3.1 Nemotron 70B Instruct (45). It leads on price. Qwen3-VL 30B-A3B 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, Llama 3.1 Nemotron 70B Instruct, Mistral Nemotron or Qwen3-VL 30B-A3B?

Mistral Nemotron is cheaper at Free input / Free output per million tokens (official Nvidia 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). Mistral Nemotron is listed as free.

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, Mistral Nemotron has not been scored yet and Qwen3-VL 30B-A3B 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, Mistral Nemotron and Qwen3-VL 30B-A3B 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 128,000 for Mistral Nemotron. Maximum output per response: Llama 3.1 Nemotron 70B Instruct up to 8,192, Mistral Nemotron up to 8,192, Qwen3-VL 30B-A3B up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Llama 3.1 Nemotron 70B Instruct accepts text; Mistral Nemotron accepts text; Qwen3-VL 30B-A3B accepts text and images. Qwen3-VL 30B-A3B handles the widest range of inputs.

Are any of these open source?

Yes, all three 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 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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