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Comparison · 3 models · Updated Oct 4, 2026

Gemma-SEA-LION-v4-27B-IT vs Llama 3.1 Nemotron 70B Instruct vs Qwen3-VL 30B-A3B

Qwen3-VL 30B-A3B comes out ahead, 59 to 45 and 39 on our weighted score, and it is the cheaper option too.

  1. AI Singapore

    Gemma-SEA-LION-v4-27B-IT

    Released Sep 23, 2025

    39/100
    • ECI—
    • Price$0.351 / $0.555
    • Context128K
    Full specs Remove Gemma-SEA-LION-v4-27B-IT

  2. 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
  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 Gemma-SEA-LION-v4-27B-IT (39). It leads on price and 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 priceQwen3-VL 30B-A3BQwen3-VL 30B-A3B $0.35 · Gemma-SEA-LION-v4-27B-IT $0.402 · Llama 3.1 Nemotron 70B Instruct $0.485 per 1M tokens (3:1 blend)
  • Longest contextQwen3-VL 30B-A3BQwen3-VL 30B-A3B 131,072 · Gemma-SEA-LION-v4-27B-IT 128,000 · Llama 3.1 Nemotron 70B Instruct 128,000 tokens
  • Widest inputsQwen3-VL 30B-A3BGemma-SEA-LION-v4-27B-IT: Text · Llama 3.1 Nemotron 70B Instruct: 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
MeasureWeightGemma-SEA-LION-v4-27B-ITLlama 3.1 Nemotron 70B InstructQwen3-VL 30B-A3B
Price50%696572
Inputs & features30%02560
Context window20%242424
Overall100%39/10045/10059/100

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.

Gemma-SEA-LION-v4-27B-IT vs Llama 3.1 Nemotron 70B Instruct vs Qwen3-VL 30B-A3B specifications side by side
SpecificationGemma-SEA-LION-v4-27B-ITAI SingaporeLlama 3.1 Nemotron 70B InstructNVIDIAQwen3-VL 30B-A3BAlibaba (Qwen)
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.351$0.478$0.20 (best)
Output$0.555$0.504 (best)$0.80
Cached input———
Blended (3:1)$0.402$0.485$0.35 (best)
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 2 providersMedian of 2 providersOfficial Alibaba API
Limits
Context window128,000 tokens128,000 tokens131,072 tokens (best)
Max output128,000 tokens (best)8,192 tokens32,768 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoYes
Tool callingNoYesYes
Structured outputNoNoNo
Availability
WeightsOpenOpenOpen
API model ID—nvidia/llama-3.1-nemotron-70b-instructqwen3-vl-30b-a3b
API providers23 (best)1
ReleasedSep 23, 2025Apr 15, 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.

  • Gemma-SEA-LION-v4-27B-IT$4.62
  • Llama 3.1 Nemotron 70B Instruct$5.79
  • Qwen3-VL 30B-A3B$3.60
04 — Questions

Which should you choose?

Which is better: Gemma-SEA-LION-v4-27B-IT, Llama 3.1 Nemotron 70B Instruct 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 Gemma-SEA-LION-v4-27B-IT (39). It leads on price and 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, Gemma-SEA-LION-v4-27B-IT, Llama 3.1 Nemotron 70B Instruct or Qwen3-VL 30B-A3B?

Qwen3-VL 30B-A3B is cheaper at $0.20 input / $0.80 output per million tokens (official Alibaba API price). Gemma-SEA-LION-v4-27B-IT costs $0.351 input / $0.555 output per million tokens (median across 2 API providers); 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 $0.35 per million tokens for Qwen3-VL 30B-A3B versus $0.402 for Gemma-SEA-LION-v4-27B-IT (1.1× as much) and $0.485 for Llama 3.1 Nemotron 70B Instruct (1.4× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Gemma-SEA-LION-v4-27B-IT has not been scored yet, Llama 3.1 Nemotron 70B Instruct 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 Gemma-SEA-LION-v4-27B-IT, Llama 3.1 Nemotron 70B Instruct 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 Gemma-SEA-LION-v4-27B-IT 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 Gemma-SEA-LION-v4-27B-IT and 128,000 for Llama 3.1 Nemotron 70B Instruct. Maximum output per response: Gemma-SEA-LION-v4-27B-IT up to 128,000, Llama 3.1 Nemotron 70B Instruct up to 8,192, Qwen3-VL 30B-A3B up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Gemma-SEA-LION-v4-27B-IT accepts text; Llama 3.1 Nemotron 70B Instruct 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?

Gemma-SEA-LION-v4-27B-IT is the newest, released Sep 23, 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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