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Comparison · 3 models · Updated Oct 4, 2026

Gemma-SEA-LION-v4-27B-IT vs GPT-5-Codex vs Seed 1.6

Seed 1.6 comes out ahead, 55 to 42 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
  2. OpenAI

    GPT-5-Codex

    Released Sep 15, 2025

    42/100
    • ECI—
    • Price$1.25 / $10.00
    • Context400K
  3. Our pick

    ByteDance Seed

    Seed 1.6

    Released Oct 15, 2025

    55/100
    • ECI—
    • Price$0.119 / $1.19
    • Context256K
01 — Verdict

Seed 1.6 is our pick

Seed 1.6 is the better all-round choice, scoring 55/100 against GPT-5-Codex (42) and Gemma-SEA-LION-v4-27B-IT (39). GPT-5-Codex wins on inputs & features and context window. 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 priceSeed 1.6Seed 1.6 $0.386 · Gemma-SEA-LION-v4-27B-IT $0.402 · GPT-5-Codex $3.44 per 1M tokens (3:1 blend)
  • Longest contextGPT-5-CodexGPT-5-Codex 400,000 · Seed 1.6 256,000 · Gemma-SEA-LION-v4-27B-IT 128,000 tokens
  • Widest inputsGPT-5-CodexGemma-SEA-LION-v4-27B-IT: Text · GPT-5-Codex: Text, Images · Seed 1.6: Text
  • Self-hostingGemma-SEA-LION-v4-27B-ITPublishes downloadable weights
How the score is built
MeasureWeightGemma-SEA-LION-v4-27B-ITGPT-5-CodexSeed 1.6
Price50%692469
Inputs & features30%07045
Context window20%244436
Overall100%39/10042/10055/100

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 GPT-5-Codex vs Seed 1.6 specifications side by side
SpecificationGemma-SEA-LION-v4-27B-ITAI SingaporeGPT-5-CodexOpenAISeed 1.6ByteDance Seed
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.351$1.25$0.119 (best)
Output$0.555 (best)$10.00$1.19
Cached input——$0.024
Blended (3:1)$0.402$3.44$0.386 (best)
Long-context rateSame rateSame rateOver 32K: $0.178 / $2.37
Price sourceMedian of 2 providersMedian of 3 providersOfficial Volcengine Ark API
Limits
Context window128,000 tokens400,000 tokens (best)256,000 tokens
Max output128,000 tokens (best)128,000 tokens (best)64,000 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoYesYesminimal · low · medium · high
Tool callingNoYesYes
Structured outputNoYesYes
Availability
WeightsOpenProprietaryProprietary
API model ID——doubao-seed-1-6-251015
API providers23 (best)2
ReleasedSep 23, 2025Sep 15, 2025Oct 15, 2025
Knowledge cutoff—Sep 30, 2024—
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
  • GPT-5-Codex$32.50
  • Seed 1.6$3.56
04 — Questions

Which should you choose?

Which is better: Gemma-SEA-LION-v4-27B-IT, GPT-5-Codex or Seed 1.6?

Seed 1.6 is the better all-round choice, scoring 55/100 against GPT-5-Codex (42) and Gemma-SEA-LION-v4-27B-IT (39). GPT-5-Codex wins on inputs & features and context window. 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, GPT-5-Codex or Seed 1.6?

Seed 1.6 is cheaper at $0.119 input / $1.19 output per million tokens (official Volcengine Ark API price). Gemma-SEA-LION-v4-27B-IT costs $0.351 input / $0.555 output per million tokens (median across 2 API providers); GPT-5-Codex costs $1.25 input / $10.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $0.386 per million tokens for Seed 1.6 versus $0.402 for Gemma-SEA-LION-v4-27B-IT (1× as much) and $3.44 for GPT-5-Codex (8.9× 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, GPT-5-Codex has not been scored yet and Seed 1.6 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, GPT-5-Codex and Seed 1.6 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?

GPT-5-Codex has the largest context window at 400,000 tokens, against 256,000 for Seed 1.6 and 128,000 for Gemma-SEA-LION-v4-27B-IT. Maximum output per response: Gemma-SEA-LION-v4-27B-IT up to 128,000, GPT-5-Codex up to 128,000, Seed 1.6 up to 64,000 tokens.

Which can read images, PDFs, audio or video?

Gemma-SEA-LION-v4-27B-IT accepts text; GPT-5-Codex accepts text and images; Seed 1.6 accepts text. GPT-5-Codex handles the widest range of inputs.

Are any of these open source?

Gemma-SEA-LION-v4-27B-IT publishes its weights and can be self-hosted; GPT-5-Codex and Seed 1.6 is proprietary.

Which is newer?

Seed 1.6 is the newest, released Oct 15, 2025. Gemma-SEA-LION-v4-27B-IT came out Sep 23, 2025; GPT-5-Codex came out Sep 15, 2025. Knowledge cutoff: GPT-5-Codex Sep 30, 2024.

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.