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Qwen · open-weights

Qwen3-8B

Qwen3-8B is an open-weights language model from Qwen, released April 28, 2025. It has 8.2B parameters (dense). The context window is 128K tokens. On the Epoch Capabilities Index it scores 132.1, rank 152 of 256 rated models. API price: $0.18 input / $0.7 output per million tokens.

Check it against your own PC →

Lab
Qwen
Released
April 28, 2025
Weights
Open apache-2.0
Parameters
8.2B dense
Context
128K
Price / M tokens
$0.18 / $0.7 in / out
Epoch ECI
132.1 #152

Can you run Qwen3-8B locally?

The smallest common GPU it runs on is 6 GB of VRAM (with 32 GB of RAM): Q6_K, split GPU / CPU, roughly 6 tokens per second. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.

GPU memoryVerdictBest quantVRAMRAMtok/s
6 GB VRAMRuns, slowlyQ6_K (≈ lossless)5.2 GB4.5 GB~6
8 GB VRAMRuns on GPUQ3_K_M (okay)7.0 GB–~39
12 GB VRAMRuns on GPUQ6_K (≈ lossless)9.7 GB–~31
16 GB VRAMRuns on GPUQ6_K (≈ lossless)9.7 GB–~43
24 GB VRAMRuns on GPUQ6_K (≈ lossless)9.7 GB–~77
32 GB VRAMRuns on GPUQ6_K (≈ lossless)9.7 GB–~140

Ready-made quantizations on Hugging Face: Qwen/Qwen3-Embedding-8B-GGUF · mradermacher/Qwen3-8B-Base-GGUF · Mungert/Qwen3-Reranker-8B-GGUF · QuantFactory/Qwen3-Reranker-8B-GGUF · mradermacher/Qwen3-8B-Base-i1-GGUF · QuantFactory/Qwen3-8B-GGUF

Benchmark results

Benchmark (Epoch AI)Score
OTIS Mock AIME56.1%
GPQA Diamond44.1%

Links

Hugging Face: Qwen/Qwen3-8B-Base · Epoch AI benchmarks

Models with a similar score

Gemini 2.0 Pro · o1-mini · DeepSeek-V3 (Mar 2025) · Qwen3-30B-A3B-Instruct (Jul 2025) · gpt-oss-20b · GPT-4.1 mini · Qwen3-30B-A3B · Gemini 2.0 Flash (Feb 2025)

More from Qwen

Qwen3.8 Omni Flash · Qwen3.8 Max (0902) · Qwen3.8 Flash · Qwen3.8 Flash Next · Qwen 3.8 27B · Qwen3.8-2.4T-A95B · Qwen 3.8 Max · Qwen3.7 Flash

Data updated Thu, 12 Nov 2026 09:42 UTC. Benchmarks, Capabilities Index and model announcements: Epoch AI, “Capabilities & benchmarking” and “Data on AI models” (CC BY 4.0); category scores are ModelTape's own fit on Epoch's results. Releases and prices: models.dev (MIT). Sizes and quantizations: Hugging Face. “Runs on” figures are estimates from model size, quantization and memory bandwidth (±30–50%).
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