Compare / MiniCPM-V 4.7 35B-A3B vs Kimi Linear 48B-A3B

MiniCPM-V 4.7 35B-A3B vs Kimi Linear 48B-A3B

Updated November 2026

Verdict

MiniCPM-V 4.7 35B-A3B scores higher on the Small LM Index: 56.7 vs 36.6. On the 5 benchmarks both labs report, MiniCPM-V 4.7 35B-A3B wins 5 and Kimi Linear 48B-A3B wins 0. MiniCPM-V 4.7 35B-A3B is smaller: it needs about 22.7 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 MiniCPM-V 4.7 35B-A3B 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 22.7 GB at 4-bit)
you need image input
you want the more widely used model (more quantized builds and community support)

Pick Kimi Linear 48B-A3B if…

you work with long documents

Specifications

	MiniCPM-V 4.7 35B-A3B	Kimi Linear 48B-A3B
Small LM Index	56.7 (likely 54–59)	36.6 (likely 34–40)
Lab	OpenBMB (MiniCPM) · China	Moonshot AI (Kimi) · China
Released	2026-10-07	2025-10-30
Parameters	35.2B (3B active, MoE)	48B (3B active, MoE)
Memory at 4-bit	~22.7 GB	~30.8 GB
Context window	262K tokens	1M tokens
Input	text, image, video	text
Reasoning	Hybrid (thinking on/off)	No thinking
License	Apache-2.0	MIT
API price / 1M tokens	Self-host only	Self-host only
Hugging Face downloads (30 days)	521.5K	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	MiniCPM-V 4.7 35B-A3B	Kimi Linear 48B-A3B
MMLU-Pro Knowledge	83.5	58.5^✓
GPQA Diamond Knowledge	≈ 66	41.2^✓
Humanity's Last Exam Reasoning	≈ 9	2.5^✓
AIME Math	76.5	36.3^✓
LiveCodeBench Coding	56.6	37.8^✓
τ²-Bench Agentic	84.7	0.0^✓
IFBench Instruction following	47.7	28.1^✓
BFCL Agentic	60.1	—
AA-LCR Long context	—	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, MiniCPM-V 4.7 35B-A3B or Kimi Linear 48B-A3B?

MiniCPM-V 4.7 35B-A3B scores higher on the Small LM Index: 56.7 vs 36.6. On the 5 benchmarks both labs report, MiniCPM-V 4.7 35B-A3B wins 5 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. MiniCPM-V 4.7 35B-A3B is smaller: it needs about 22.7 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 262K.

Can I use MiniCPM-V 4.7 35B-A3B and Kimi Linear 48B-A3B commercially?

MiniCPM-V 4.7 35B-A3B 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.