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Comparison · 2 models · Updated Oct 4, 2026

Llama 3.3 Nemotron Super 49B v1.5 vs Gemma-SEA-LION-v4-27B-IT

Llama 3.3 Nemotron Super 49B v1.5 comes out ahead, 50 to 39 on our weighted score, and it is the cheaper option too.

  1. Our pick

    NVIDIA

    Llama 3.3 Nemotron Super 49B v1.5

    Released Jul 25, 2025Deprecated

    50/100
    • ECI—
    • Price$0.40 / $0.40
    • Context131K
    Full specs Remove Llama 3.3 Nemotron Super 49B v1.5

  2. 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

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Llama 3.3 Nemotron Super 49B v1.5 is our pick

Llama 3.3 Nemotron Super 49B v1.5 is the better all-round choice, scoring 50/100 against Gemma-SEA-LION-v4-27B-IT (39). It leads 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 priceLlama 3.3 Nemotron Super 49B v1.5Llama 3.3 Nemotron Super 49B v1.5 $0.40 · Gemma-SEA-LION-v4-27B-IT $0.402 per 1M tokens (3:1 blend)
  • Longest contextLlama 3.3 Nemotron Super 49B v1.5Llama 3.3 Nemotron Super 49B v1.5 131,072 · Gemma-SEA-LION-v4-27B-IT 128,000 tokens
  • Widest inputsSame inputsLlama 3.3 Nemotron Super 49B v1.5: Text · Gemma-SEA-LION-v4-27B-IT: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightLlama 3.3 Nemotron Super 49B v1.5Gemma-SEA-LION-v4-27B-IT
Price50%6969
Inputs & features30%350
Context window20%2424
Overall100%50/10039/100

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 3.3 Nemotron Super 49B v1.5 vs Gemma-SEA-LION-v4-27B-IT specifications side by side
SpecificationLlama 3.3 Nemotron Super 49B v1.5NVIDIAGemma-SEA-LION-v4-27B-ITAI Singapore
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.40$0.351 (best)
Output$0.40 (best)$0.555
Cached input——
Blended (3:1)$0.40 (best)$0.402
Long-context rateSame rateSame rate
Price sourceMedian of 1 providersMedian of 2 providers
Limits
Context window131,072 tokens (best)128,000 tokens
Max output131,072 tokens (best)128,000 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesNo
Tool callingYesNo
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDnvidia/llama-3.3-nemotron-super-49b-v1.5—
API providers22
ReleasedJul 25, 2025Sep 23, 2025
Knowledge cutoff——
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 3.3 Nemotron Super 49B v1.5$4.80
  • Gemma-SEA-LION-v4-27B-IT$4.62
04 — Questions

Which should you choose?

Which is better: Llama 3.3 Nemotron Super 49B v1.5 or Gemma-SEA-LION-v4-27B-IT?

Llama 3.3 Nemotron Super 49B v1.5 is the better all-round choice, scoring 50/100 against Gemma-SEA-LION-v4-27B-IT (39). It leads 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 3.3 Nemotron Super 49B v1.5 or Gemma-SEA-LION-v4-27B-IT?

Llama 3.3 Nemotron Super 49B v1.5 is cheaper at $0.40 input / $0.40 output per million tokens (median across 1 API provider; free on Nvidia). Gemma-SEA-LION-v4-27B-IT costs $0.351 input / $0.555 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.40 per million tokens for Llama 3.3 Nemotron Super 49B v1.5 versus $0.402 for Gemma-SEA-LION-v4-27B-IT (1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Llama 3.3 Nemotron Super 49B v1.5 has not been scored yet and Gemma-SEA-LION-v4-27B-IT has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Llama 3.3 Nemotron Super 49B v1.5 and Gemma-SEA-LION-v4-27B-IT 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?

Llama 3.3 Nemotron Super 49B v1.5 has the largest context window at 131,072 tokens, against 128,000 for Gemma-SEA-LION-v4-27B-IT. Maximum output per response: Llama 3.3 Nemotron Super 49B v1.5 up to 131,072, Gemma-SEA-LION-v4-27B-IT up to 128,000 tokens.

Which can read images, PDFs, audio or video?

Llama 3.3 Nemotron Super 49B v1.5 accepts text; Gemma-SEA-LION-v4-27B-IT accepts text. They handle the same number of input types.

Are any of these open source?

Yes, both 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 3.3 Nemotron Super 49B v1.5 came out Jul 25, 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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