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Comparison · 3 models · Updated Oct 4, 2026

Llama 3.1 Nemotron 70B Instruct vs Qwen3-VL 30B-A3B vs Solar Pro 2

Qwen3-VL 30B-A3B comes out ahead, 59 to 52 and 45 on our weighted score, though Solar Pro 2 is 29% 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. Upstage

    Solar Pro 2

    Released May 20, 2025

    52/100
    • ECI—
    • Price$0.25 / $0.25
    • Context66K
    Full specs Remove Solar Pro 2
01 — Verdict

Qwen3-VL 30B-A3B is our pick

Qwen3-VL 30B-A3B is the better all-round choice, scoring 59/100 against Solar Pro 2 (52) and Llama 3.1 Nemotron 70B Instruct (45). It leads on inputs & features. Solar Pro 2 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 priceSolar Pro 2Solar Pro 2 $0.25 · 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 · Solar Pro 2 65,536 tokens
  • Widest inputsQwen3-VL 30B-A3BLlama 3.1 Nemotron 70B Instruct: Text · Qwen3-VL 30B-A3B: Text, Images · Solar Pro 2: Text
  • Self-hostingLlama 3.1 Nemotron 70B Instruct and Qwen3-VL 30B-A3BPublishes downloadable weights
How the score is built
MeasureWeightLlama 3.1 Nemotron 70B InstructQwen3-VL 30B-A3BSolar Pro 2
Price50%657278
Inputs & features30%256035
Context window20%242412
Overall100%45/10059/10052/100

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 Solar Pro 2 specifications side by side
SpecificationLlama 3.1 Nemotron 70B InstructNVIDIAQwen3-VL 30B-A3BAlibaba (Qwen)Solar Pro 2Upstage
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.478$0.20 (best)$0.25
Output$0.504$0.80$0.25 (best)
Cached input———
Blended (3:1)$0.485$0.35$0.25 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Alibaba APIOfficial Upstage API
Limits
Context window128,000 tokens131,072 tokens (best)65,536 tokens
Max output8,192 tokens32,768 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoYesYesminimal · high
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenProprietary
API model IDnvidia/llama-3.1-nemotron-70b-instructqwen3-vl-30b-a3bsolar-pro2
API providers3 (best)12
ReleasedApr 15, 2025Apr 2025May 20, 2025
Knowledge cutoff—Apr 2025Mar 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
  • Solar Pro 2$3.00
04 — Questions

Which should you choose?

Which is better: Llama 3.1 Nemotron 70B Instruct, Qwen3-VL 30B-A3B or Solar Pro 2?

Qwen3-VL 30B-A3B is the better all-round choice, scoring 59/100 against Solar Pro 2 (52) and Llama 3.1 Nemotron 70B Instruct (45). It leads on inputs & features. Solar Pro 2 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 Solar Pro 2?

Solar Pro 2 is cheaper at $0.25 input / $0.25 output per million tokens (official Upstage 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 $0.25 per million tokens for Solar Pro 2 versus $0.35 for Qwen3-VL 30B-A3B (1.4× as much) and $0.485 for Llama 3.1 Nemotron 70B Instruct (1.9× 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 Solar Pro 2 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 Solar Pro 2 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 65,536 for Solar Pro 2. Maximum output per response: Llama 3.1 Nemotron 70B Instruct up to 8,192, Qwen3-VL 30B-A3B up to 32,768, Solar Pro 2 up to 8,192 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; Solar Pro 2 accepts text. 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; Solar Pro 2 is proprietary.

Which is newer?

Solar Pro 2 is the newest, released May 20, 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, Solar Pro 2 Mar 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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