Compare / Seed-OSS 36B Instruct vs Kimi Linear 48B-A3B

Seed-OSS 36B Instruct vs Kimi Linear 48B-A3B

Updated November 2026

Verdict

Seed-OSS 36B Instruct scores higher on the Small LM Index: 61.5 vs 36.6. On the 8 benchmarks both labs report, Seed-OSS 36B Instruct wins 8 and Kimi Linear 48B-A3B wins 0. Seed-OSS 36B Instruct is smaller: it needs about 25.3 GB of memory at 4-bit, against 30.8 GB for Kimi Linear 48B-A3B. Neither model has a hosted API on OpenRouter, so you would run both yourself.

Pick Seed-OSS 36B Instruct if…

you want the strongest model overall
you mostly write code
you need math and reasoning
you need precise instruction following
you build agents that call tools
you have limited memory (about 25.3 GB at 4-bit)

Pick Kimi Linear 48B-A3B if…

you work with long documents

Specifications

	Seed-OSS 36B Instruct	Kimi Linear 48B-A3B
Small LM Index	61.5 (likely 59–64)	36.6 (likely 34–40)
Lab	ByteDance Seed · China	Moonshot AI (Kimi) · China
Released	2025-08-20	2025-10-30
Parameters	36.2B (dense)	48B (3B active, MoE)
Memory at 4-bit	~25.3 GB	~30.8 GB
Context window	512K tokens	1M tokens
Input	text	text
Reasoning	Always thinks	No thinking
License	Apache-2.0	MIT
API price / 1M tokens	Self-host only	Self-host only
Hugging Face downloads (30 days)	40.6K	69K

Benchmarks

Higher is better. Bold marks the winner where both labs report a score. ≈ marks the index model's estimate for a score that wasn't reported, ✓ an independent measurement and * a score measured by another lab.

Benchmark	Seed-OSS 36B Instruct	Kimi Linear 48B-A3B
MMLU-Pro Knowledge	81.5^✓	58.5^✓
GPQA Diamond Knowledge	72.6^✓	41.2^✓
Humanity's Last Exam Reasoning	9.9^✓	2.5^✓
AIME Math	84.7^✓	36.3^✓
LiveCodeBench Coding	76.5^✓	37.8^✓
SWE-bench Verified Coding	56.0	≈ 40
τ²-Bench Agentic	49.4^✓	0.0^✓
IFBench Instruction following	41.9^✓	28.1^✓
MMLU Knowledge	87.4	—
Multilingual MMLU Multilingual	78.4	—
IFEval Instruction following	85.8	—
AA-LCR Long context	61.3^✓	28.0^✓

Scores are mostly reported by each lab with its own settings, so small gaps are noise. See the methodology. Open in the interactive comparison to add more models.

Questions

Which is better, Seed-OSS 36B Instruct or Kimi Linear 48B-A3B?

Seed-OSS 36B Instruct scores higher on the Small LM Index: 61.5 vs 36.6. On the 8 benchmarks both labs report, Seed-OSS 36B Instruct wins 8 and Kimi Linear 48B-A3B wins 0.

Which is cheaper to run?

Neither model has a hosted API on OpenRouter, so you would run both yourself. Seed-OSS 36B Instruct is smaller: it needs about 25.3 GB of memory at 4-bit, against 30.8 GB for Kimi Linear 48B-A3B.

Which has the longer context window?

Kimi Linear 48B-A3B has the longer context window: 1M tokens against 512K.

Can I use Seed-OSS 36B Instruct and Kimi Linear 48B-A3B commercially?

Seed-OSS 36B Instruct is released under Apache-2.0 and Kimi Linear 48B-A3B under MIT. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.