Qwen3 Coder REAP 25B A3B — Hardware Requirements & GPU Compatibility
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Qwen3 Coder REAP 25B A3B is a 24.9B-parameter open language model from Cerebras in the Qwen 3 family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 15.32 GB of VRAM — see which GPUs and Macs can run it below.
574 downloads
86 likesSpecifications
- Publisher
- Cerebras
- Family
- Qwen 3
- Parameters
- 24.9B
- Architecture
- Qwen3MoeForCausalLM
- Context Length
- 262,144 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2025-10-20
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Qwen3 Coder REAP 25B A3B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 11.0 GB | 23.8 GB | 10.57 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 12.5 GB | 25.3 GB | 12.12 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 15.3 GB | 28.1 GB | 14.92 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 18.1 GB | 30.9 GB | 17.72 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 20.9 GB | 33.7 GB | 20.52 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 25.3 GB | 38.0 GB | 24.87 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 50.1 GB | 62.9 GB | 49.73 GB | Brain floating point 16 — preferred for training |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Qwen3 Coder REAP 25B A3B?
Q4_K_M · 15.3 GBQwen3 Coder REAP 25B A3B (Q4_K_M) requires 15.3 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 20+ GB is recommended. Using the full 262K context window can add up to 12.8 GB, bringing total usage to 28.1 GB. 26 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 5080.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Qwen3 Coder REAP 25B A3B?
Q4_K_M · 15.3 GB47 devices with unified memory can run Qwen3 Coder REAP 25B A3B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 (16 GB).
Runs great
— Plenty of headroomRelated Models
Frequently Asked Questions
- How much VRAM does Qwen3 Coder REAP 25B A3B need?
Qwen3 Coder REAP 25B A3B requires 15.3 GB of VRAM at Q4_K_M, or 50.1 GB at BF16. Full 262K context adds up to 12.8 GB (28.1 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 24.9B × 4.8 bits ÷ 8 = 14.9 GB
KV Cache + Overhead ≈ 0.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 13.2 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M15.3 GBQ4_K_M + full context28.1 GB- Can NVIDIA GeForce RTX 4090 run Qwen3 Coder REAP 25B A3B?
Yes, at Q6_K (20.9 GB) or lower. Higher quantizations like Q8_0 (25.3 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Qwen3 Coder REAP 25B A3B?
For Qwen3 Coder REAP 25B A3B, Q4_K_M (15.3 GB) offers the best balance of quality and VRAM usage. Q5_K_M (18.1 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 11.0 GB.
VRAM requirement by quantization
Q2_K11.0 GBQ4_K_M ★15.3 GBQ5_K_M18.1 GBQ6_K20.9 GBQ8_025.3 GBBF1650.1 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Qwen3 Coder REAP 25B A3B on a Mac?
Qwen3 Coder REAP 25B A3B requires at least 11.0 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Qwen3 Coder REAP 25B A3B locally?
Yes — Qwen3 Coder REAP 25B A3B can run locally on consumer hardware. At Q4_K_M quantization it needs 15.3 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Qwen3 Coder REAP 25B A3B?
At Q4_K_M, Qwen3 Coder REAP 25B A3B can reach ~313 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~43 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 15.3 × 0.65 = ~339 tok/s
Estimated speed at Q4_K_M (15.3 GB)
~339 tok/s~43 tok/s~339 tok/s~313 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Qwen3 Coder REAP 25B A3B?
At Q4_K_M, the download is about 14.92 GB. The full-precision BF16 version is 49.73 GB. The smallest option (Q2_K) is 10.57 GB.
- Which GPUs can run Qwen3 Coder REAP 25B A3B?
26 consumer GPUs can run Qwen3 Coder REAP 25B A3B at Q4_K_M (15.3 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090, NVIDIA GeForce RTX 3090 Ti, AMD Radeon RX 6800. 7 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Qwen3 Coder REAP 25B A3B?
49 devices with unified memory can run Qwen3 Coder REAP 25B A3B at Q4_K_M (15.3 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.