Baichuan M3 235B — Hardware Requirements & GPU Compatibility
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Baichuan M3 235B is a 235.1B-parameter open language model from baichuan-inc in the Baichuan family. It supports a context window of up to 40,960 tokens. At Q4_K_M it needs about 141.55 GB of VRAM — see which GPUs and Macs can run it below.
1.9K downloads
93 likesSpecifications
- Publisher
- baichuan-inc
- Family
- Baichuan
- Parameters
- 235.1B
- Architecture
- Qwen3MoeForCausalLM
- Context Length
- 40,960 tokens
- Vocabulary Size
- 151,936
- Release Date
- 2026-01-13
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Baichuan M3 235B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_Kest. | 3.40 | 100.4 GB | 104.2 GB | 99.91 GB | 2-bit quantization with K-quant improvements |
| Q3_K_Mest. | 3.90 | 115.1 GB | 118.8 GB | 114.61 GB | 3-bit medium quantization |
| Q4_K_Mest. | 4.80 | 141.6 GB | 145.3 GB | 141.06 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_Mest. | 5.70 | 168 GB | 171.8 GB | 167.50 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_Kest. | 6.60 | 194.4 GB | 198.2 GB | 193.95 GB | 6-bit quantization, very good quality |
| Q8_0est. | 8.00 | 235.6 GB | 239.3 GB | 235.09 GB | 8-bit quantization, near-lossless |
| BF16est. | 16.00 | 470.7 GB | 474.4 GB | 470.19 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 Baichuan M3 235B?
Q4_K_M · 141.6 GBBaichuan M3 235B (Q4_K_M) requires 141.6 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 185+ GB is recommended. Using the full 41K context window can add up to 3.8 GB, bringing total usage to 145.3 GB. No single GPU has enough memory — multi-GPU or cluster setups are needed.
Which Devices Can Run Baichuan M3 235B?
Q4_K_M · 141.6 GB4 devices with unified memory can run Baichuan M3 235B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Pro M2 Ultra (192 GB).
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightRelated Models
Frequently Asked Questions
- How much VRAM does Baichuan M3 235B need?
Baichuan M3 235B requires 141.6 GB of VRAM at Q4_K_M, or 470.7 GB at BF16. Full 41K context adds up to 3.8 GB (145.3 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 235.1B × 4.8 bits ÷ 8 = 141.1 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 4.2 GB (at full 41K context)
VRAM usage by quantization
Q4_K_M141.6 GBQ4_K_M + full context145.3 GB- Can NVIDIA GeForce RTX 5090 run Baichuan M3 235B?
No — Baichuan M3 235B requires at least 100.4 GB at Q2_K, which exceeds the NVIDIA GeForce RTX 5090's 32 GB of VRAM.
- What's the best quantization for Baichuan M3 235B?
For Baichuan M3 235B, Q4_K_M (141.6 GB) offers the best balance of quality and VRAM usage. Q5_K_M (168 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 100.4 GB.
VRAM requirement by quantization
Q2_K100.4 GBQ4_K_M ★141.6 GBQ5_K_M168.0 GBQ6_K194.4 GBQ8_0235.6 GBBF16470.7 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Baichuan M3 235B on a Mac?
Baichuan M3 235B requires at least 100.4 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 Baichuan M3 235B locally?
Yes — Baichuan M3 235B can run locally on consumer hardware. At Q4_K_M quantization it needs 141.6 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Baichuan M3 235B?
At Q4_K_M, Baichuan M3 235B can reach ~21 tok/s on AMD Instinct MI300X. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: AMD Instinct MI300X → 5300 ÷ 141.6 × 0.55 = ~21 tok/s
Estimated speed at Q4_K_M (141.6 GB)
~21 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Baichuan M3 235B?
At Q4_K_M, the download is about 141.06 GB. The full-precision BF16 version is 470.19 GB. The smallest option (Q2_K) is 99.91 GB.
- Which GPUs can run Baichuan M3 235B?
No single consumer GPU has enough VRAM to run Baichuan M3 235B at Q4_K_M (141.6 GB). Multi-GPU or professional hardware is required.
- Which devices can run Baichuan M3 235B?
4 devices with unified memory can run Baichuan M3 235B at Q4_K_M (141.6 GB), including Mac Pro M2 Ultra (192 GB), Mac Studio M2 Ultra (192 GB), NVIDIA DGX A100 640GB, NVIDIA DGX H100. Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.