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Comparison · 3 models · Updated Oct 4, 2026

Llama 3.1 Nemotron 70B Instruct vs Qwen-MT Turbo vs Qwen3-VL 30B-A3B

Qwen3-VL 30B-A3B comes out ahead, 59 to 45 and 40 on our weighted score, though Qwen-MT Turbo is 31% 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. Alibaba (Qwen)

    Qwen-MT Turbo

    Released Jan 2025

    40/100
    • ECI—
    • Price$0.16 / $0.49
    • Context16K
    Full specs Remove Qwen-MT Turbo
  3. 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
01 — Verdict

Qwen3-VL 30B-A3B is our pick

Qwen3-VL 30B-A3B is the better all-round choice, scoring 59/100 against Llama 3.1 Nemotron 70B Instruct (45) and Qwen-MT Turbo (40). It leads on inputs & features. Qwen-MT Turbo 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 priceQwen-MT TurboQwen-MT Turbo $0.242 · 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 · Qwen-MT Turbo 16,384 tokens
  • Widest inputsQwen3-VL 30B-A3BLlama 3.1 Nemotron 70B Instruct: Text · Qwen-MT Turbo: Text · Qwen3-VL 30B-A3B: Text, Images
  • Self-hostingLlama 3.1 Nemotron 70B Instruct and Qwen3-VL 30B-A3BPublishes downloadable weights
How the score is built
MeasureWeightLlama 3.1 Nemotron 70B InstructQwen-MT TurboQwen3-VL 30B-A3B
Price50%657972
Inputs & features30%25060
Context window20%24024
Overall100%45/10040/10059/100

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 Qwen-MT Turbo vs Qwen3-VL 30B-A3B specifications side by side
SpecificationLlama 3.1 Nemotron 70B InstructNVIDIAQwen-MT TurboAlibaba (Qwen)Qwen3-VL 30B-A3BAlibaba (Qwen)
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.478$0.16 (best)$0.20
Output$0.504$0.49 (best)$0.80
Cached input———
Blended (3:1)$0.485$0.242 (best)$0.35
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Alibaba APIOfficial Alibaba API
Limits
Context window128,000 tokens16,384 tokens131,072 tokens (best)
Max output8,192 tokens8,192 tokens32,768 tokens (best)
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoYes
Tool callingYesNoYes
Structured outputNoNoNo
Availability
WeightsOpenProprietaryOpen
API model IDnvidia/llama-3.1-nemotron-70b-instructqwen-mt-turboqwen3-vl-30b-a3b
API providers3 (best)11
ReleasedApr 15, 2025Jan 2025Apr 2025
Knowledge cutoff—Apr 2024Apr 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
  • Qwen-MT Turbo$2.58
  • Qwen3-VL 30B-A3B$3.60
04 — Questions

Which should you choose?

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

Qwen3-VL 30B-A3B is the better all-round choice, scoring 59/100 against Llama 3.1 Nemotron 70B Instruct (45) and Qwen-MT Turbo (40). It leads on inputs & features. Qwen-MT Turbo 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, Qwen-MT Turbo or Qwen3-VL 30B-A3B?

Qwen-MT Turbo is cheaper at $0.16 input / $0.49 output per million tokens (official Alibaba 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 $0.242 per million tokens for Qwen-MT Turbo versus $0.35 for Qwen3-VL 30B-A3B (1.4× as much) and $0.485 for Llama 3.1 Nemotron 70B Instruct (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, Qwen-MT Turbo 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, Qwen-MT Turbo and Qwen3-VL 30B-A3B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen-MT Turbo does not support tool calling, which most coding agents need.

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 16,384 for Qwen-MT Turbo. Maximum output per response: Llama 3.1 Nemotron 70B Instruct up to 8,192, Qwen-MT Turbo 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; Qwen-MT Turbo 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?

Llama 3.1 Nemotron 70B Instruct and Qwen3-VL 30B-A3B publishes its weights and can be self-hosted; Qwen-MT Turbo is proprietary.

Which is newer?

Llama 3.1 Nemotron 70B Instruct is the newest, released Apr 15, 2025. Qwen3-VL 30B-A3B came out Apr 2025; Qwen-MT Turbo came out Jan 2025. Knowledge cutoff: Qwen-MT Turbo Apr 2024, 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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