Leaderboard / Alibaba (Qwen)

Qwen3 4B Thinking 2507

Alibaba (Qwen) · Qwen3 · released 2025-08-06 · data checked 2026-11-01 Needs verification

Qwen3 4B Thinking 2507 is a 4B-parameter dense model from Alibaba (Qwen) (China), released 2025-08-06 under the Apache-2.0 license. It scores 55.7 on the Small LM Index, #8 of 21 tiny models. It needs about 4.2 GB of memory at 4-bit with an 8K-token context.

Small LM Index
55.7
#8 of 21 scored tiny models
Likely 51.2–59.9 · from 4 of 6 core benchmarks
Parameters
4B
Dense
Price per 1M tokens
—
No hosted API on OpenRouter; self-host
Context window
262K
tokens

Benchmarks

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

MMLU-Pro Lab-reported Knowledge74.0
Class best: Qwen3.5 4B 79.1
GPQA Diamond Lab-reported Knowledge65.8
Class best: Nanbeige4.2 3B 87.4
AIME Lab-reported Math · AIME 202581.3
Class best: Spark-X2.6 4B 91.2
LiveCodeBench Lab-reported Coding · LiveCodeBench v655.2
Class best: LFM3 1.7B 73.5

Not reported: estimated

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

Humanity's Last Exam≈ 8
SWE-bench Verified≈ 39

Specifications

Lab
Alibaba (Qwen) (CN · China)
Architecture
Dense transformer
Total parameters
4B
Active parameters
All (dense)
Size class
Tiny
Context window
262K tokens
Input modalities
text
Reasoning
Reasoning (thinking)
License
Apache-2.0
Openness
Open weights
Memory to run
~4.2 GB at 4-bit, 8K context (more sizes)
Hugging Face
440.9K downloads (30 days) · 629 likes

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Sources

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Run it locally

Uses unsloth/Qwen3-4B-Thinking-2507-GGUF (Q4_K_M). Swap the tag for another size: F16, IQ4_NL, IQ4_XS, Q2_K, Q2_K_L, Q3_K_M, Q3_K_S, Q4_0….

Ollama
ollama run hf.co/unsloth/Qwen3-4B-Thinking-2507-GGUF:Q4_K_M
llama.cpp
llama-server -hf unsloth/Qwen3-4B-Thinking-2507-GGUF:Q4_K_M
Then open http://localhost:8080 for a chat window.
MLX (Mac)
pip install -U mlx-lm
mlx_lm.chat --model mlx-community/Qwen3-4B-Thinking-2507-4bit
vLLM (GPU server)
vllm serve Qwen/Qwen3-4B-Thinking-2507
Full-precision weights, for a server GPU.

Open in LM Studio

Memory needed: weights, context cache and runtime buffers.

Quantization4K context32K context256K context
16-bit F169.2 GB13 GB47 GB
8-bit Q8_05.4 GB9.7 GB43 GB
4-bit Q4_K_M3.6 GB7.8 GB42 GB

Check it against your GPU, Mac or phone →