Compare / MiniCPM5 1B vs Qwen3.5 0.8B

MiniCPM5 1B vs Qwen3.5 0.8B

Updated November 2026

Verdict

MiniCPM5 1B scores higher on the Small LM Index: 29.5 vs 14.2. On the 5 benchmarks both labs report, MiniCPM5 1B wins 4 and Qwen3.5 0.8B wins 1. Both need about 1.4 GB of memory at 4-bit quantization. Neither model has a hosted API on OpenRouter, so you would run both yourself.

Pick MiniCPM5 1B if…

  • you want the strongest model overall
  • you need precise instruction following
  • you build agents that call tools

Pick Qwen3.5 0.8B if…

  • you work with long documents
  • you need image input
  • you want the more widely used model (more quantized builds and community support)

Specifications

MiniCPM5 1BQwen3.5 0.8B
Small LM Index29.5 (likely 20–42)14.2 (likely 12–17)
LabOpenBMB (MiniCPM) · ChinaAlibaba (Qwen) · China
Released2026-05-212026-03-02
Parameters1.1B (dense)900M (dense)
Memory at 4-bit~1.4 GB~1.2 GB
Context window131K tokens262K tokens
Inputtexttext, image, video
ReasoningHybrid (thinking on/off)Hybrid (thinking on/off)
LicenseApache-2.0Apache-2.0
API price / 1M tokensSelf-host onlySelf-host only
Hugging Face downloads (30 days)257.9K3.7M

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.

BenchmarkMiniCPM5 1BQwen3.5 0.8B
MMLU-Pro Knowledge≈ 5342.3
GPQA Diamond Knowledge27.8✓11.1✓
Humanity's Last Exam Reasoning6.5✓1.1✓
τ²-Bench Agentic81.0✓47.7✓
IFBench Instruction following49.3✓21.5✓
MMMU-Pro Vision—25.8✓
MMLU Knowledge—59.5
Multilingual MMLU Multilingual—44.3
IFEval Instruction following—44.0
BFCL Agentic—25.3
AA-LCR Long context6.0✓9.0✓

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, MiniCPM5 1B or Qwen3.5 0.8B?

MiniCPM5 1B scores higher on the Small LM Index: 29.5 vs 14.2. On the 5 benchmarks both labs report, MiniCPM5 1B wins 4 and Qwen3.5 0.8B wins 1.

Which is cheaper to run?

Neither model has a hosted API on OpenRouter, so you would run both yourself. Both need about 1.4 GB of memory at 4-bit quantization.

Which has the longer context window?

Qwen3.5 0.8B has the longer context window: 262K tokens against 131K.

Can I use MiniCPM5 1B and Qwen3.5 0.8B commercially?

Both are released under the Apache-2.0 license. Apache 2.0 and MIT allow commercial use; other licenses can add conditions, so read the license before shipping a product.

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