Leaderboard / OpenBMB (MiniCPM)

MiniCPM-SALA

OpenBMB (MiniCPM) · MiniCPM · released 2026-02-11 · data checked 2026-11-02

MiniCPM-SALA is a 9.5B-parameter dense model from OpenBMB (MiniCPM) (China), released 2026-02-11 under the Apache-2.0 license. It scores 52.6 on the Small LM Index, #10 of 26 small models. It needs about 6.7 GB of memory at 4-bit with an 8K-token context.

Long-context model mixing sparse (25%) and linear (75%) attention for million-token contexts; up to 3.5x faster than Qwen3-8B at 256K tokens.

Small LM Index
52.6
#10 of 26 scored small models
Likely 47.8–57.3 · from 3 of 6 core benchmarks
Parameters
9.5B
Dense
Price per 1M tokens
—
No hosted API on OpenRouter; self-host
Context window
1M
tokens

Benchmarks

Each bar shows this model's score. The tick marks the best small model on that benchmark. Sources: 4 reported by OpenBMB (MiniCPM). How we label sources.

MMLU-Pro Lab-reported Knowledge67.0
Class best: Qwen3.5 9B 82.5
AIME Lab-reported Math · AIME 202578.3
Class best: Apriel 1.6 15B Thinker 88.0
LiveCodeBench Lab-reported Coding · LiveCodeBench v652.0
Class best: Granite 4.2 8B 73.2
IFEval Lab-reported Instruction following76.3
Class best: LFM2.5 8B-A1B 91.8

Not reported: estimated

What the index model expects from this model's other scores. Not a measurement.

GPQA Diamond≈ 66
Humanity's Last Exam≈ 7
SWE-bench Verified≈ 35

Specifications

Lab
OpenBMB (MiniCPM) (CN · China)
Architecture
Dense transformer
Total parameters
9.5B
Active parameters
All (dense)
Size class
Small
Context window
1M tokens
Input modalities
text
Reasoning
Hybrid (thinking on/off)
License
Apache-2.0
Openness
Open weights
Memory to run
~6.7 GB at 4-bit, 8K context (more sizes)
Hugging Face
3.7K downloads (30 days) · 686 likes

Compare with

Sources

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Run it locally

No GGUF build from a well-known publisher yet.

vLLM (GPU server)
vllm serve openbmb/MiniCPM-SALA
Full-precision weights, for a server GPU.

Memory needed: weights, context cache and runtime buffers.

Quantization4K context32K context256K context
16-bit F1620 GB21 GB28 GB
8-bit Q8_011 GB12 GB19 GB
4-bit Q4_K_M6.6 GB7.5 GB15 GB

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