ZMIME
Comparison · 2 models · Updated Nov 2, 2026

Seed-OSS-36B-Instruct vs Qwen3 235B-A22B Thinking 2507

Qwen3 235B-A22B Thinking 2507 comes out ahead, 67 to 60 on our weighted score, and it is the cheaper option too.

  1. ByteDance Seed

    Seed-OSS-36B-Instruct

    Released Aug 20, 2025

    60/100
    • ECI—
    • Price—
    • Context524K
  2. Our pick

    Alibaba (Qwen)

    Qwen3 235B-A22B Thinking 2507

    Released Jul 25, 2025

    67/100
    • ECI143.8
    • Price$0.30 / $2.90
    • Context262K
  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen3 235B-A22B Thinking 2507 is our pick

Qwen3 235B-A22B Thinking 2507 is the better all-round choice, scoring 67/100 against Seed-OSS-36B-Instruct (60). It leads on capability. Seed-OSS-36B-Instruct wins on context window. The score weighs capability 67%, inputs & features 20%, context window 13%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Seed-OSS-36B-Instruct has no Capabilities Index score yet.

  • CapabilityQwen3 235B-A22B Thinking 2507Shared benchmarks: Qwen3 235B-A22B Thinking 2507 83.4% · Seed-OSS-36B-Instruct 69.5%
  • Lowest priceQwen3 235B-A22B Thinking 2507Qwen3 235B-A22B Thinking 2507 $0.95 per 1M tokens (3:1 blend) · Seed-OSS-36B-Instruct unpriced
  • Longest contextSeed-OSS-36B-InstructSeed-OSS-36B-Instruct 524,288 · Qwen3 235B-A22B Thinking 2507 262,144 tokens
  • Widest inputsSame inputsSeed-OSS-36B-Instruct: Text · Qwen3 235B-A22B Thinking 2507: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightSeed-OSS-36B-InstructQwen3 235B-A22B Thinking 2507
CapabilityShared benchmarks67%7083
Inputs & features20%3535
Context window13%4937
Overall100%60/10067/100

Left out because at least one model lacks the data: price. 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.

Seed-OSS-36B-Instruct vs Qwen3 235B-A22B Thinking 2507 specifications side by side
SpecificationSeed-OSS-36B-InstructByteDance SeedQwen3 235B-A22B Thinking 2507Alibaba (Qwen)
Capability
Capabilities Index (ECI)—143.8
ECI rank—#93 of 165
GPQA DiamondGraduate-level science questions71.5%80.1% (best)
OTIS Mock AIME 2024–2025Competition mathematics67.5%86.7% (best)
SimpleQA VerifiedShort factual questions—40.4%
Price per million tokens
Input—$0.30
Output—$2.90
Cached input——
Blended (3:1)—$0.95
Long-context rate—Same rate
Price source—Median of 11 providers
Limits
Context window524,288 tokens (best)262,144 tokens
Max output524,288 tokens (best)81,920 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesYes
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenApache 2.0OpenApache 2.0
API model ID——
API providers—12
ReleasedAug 20, 2025Jul 25, 2025
Knowledge cutoffJul 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.

  • Seed-OSS-36B-Instruct—
  • Qwen3 235B-A22B Thinking 2507$8.80
04 — Questions

Which should you choose?

Which is better: Seed-OSS-36B-Instruct or Qwen3 235B-A22B Thinking 2507?

Qwen3 235B-A22B Thinking 2507 is the better all-round choice, scoring 67/100 against Seed-OSS-36B-Instruct (60). It leads on capability. Seed-OSS-36B-Instruct wins on context window. The score weighs capability 67%, inputs & features 20%, context window 13%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Seed-OSS-36B-Instruct has no Capabilities Index score yet.

Which is cheaper, Seed-OSS-36B-Instruct or Qwen3 235B-A22B Thinking 2507?

Qwen3 235B-A22B Thinking 2507 is cheaper at $0.30 input / $2.90 output per million tokens (median across 11 API providers). . At a typical mix of three input tokens to one output token, that is $0.95 per million tokens for Qwen3 235B-A22B Thinking 2507 versus . Seed-OSS-36B-Instruct has no published per-token price.

Which scores higher on benchmarks?

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): Qwen3 235B-A22B Thinking 2507 83.4% and Seed-OSS-36B-Instruct 69.5%. On individual benchmarks: GPQA Diamond — Qwen3 235B-A22B Thinking 2507 80.1%, Seed-OSS-36B-Instruct 71.5%; OTIS Mock AIME 2024–2025 — Qwen3 235B-A22B Thinking 2507 86.7%, Seed-OSS-36B-Instruct 67.5%.

Which is better for coding?

There are no published SWE-bench Verified results for Seed-OSS-36B-Instruct and Qwen3 235B-A22B Thinking 2507 yet, so there is no like-for-like coding score. On overall capability, Qwen3 235B-A22B Thinking 2507 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

Seed-OSS-36B-Instruct has the largest context window at 524,288 tokens, against 262,144 for Qwen3 235B-A22B Thinking 2507. Maximum output per response: Seed-OSS-36B-Instruct up to 524,288, Qwen3 235B-A22B Thinking 2507 up to 81,920 tokens.

Which can read images, PDFs, audio or video?

Seed-OSS-36B-Instruct accepts text; Qwen3 235B-A22B Thinking 2507 accepts text. They handle the same number of input types.

Are any of these open source?

Yes, both publish their weights (Apache 2.0), so you can self-host them.

Which is newer?

Seed-OSS-36B-Instruct is the newest, released Aug 20, 2025. Qwen3 235B-A22B Thinking 2507 came out Jul 25, 2025. Knowledge cutoff: Seed-OSS-36B-Instruct Jul 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 Nov 2, 2026.