Tmax 9B — Hardware Requirements & GPU Compatibility
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Tmax 9B is a 9.0B-parameter open language model from Allen AI in the Tmax family. It supports a context window of up to 262,144 tokens. At Q4_K_M it needs about 5.94 GB of VRAM — see which GPUs and Macs can run it below.
26.5K downloads
10 likesSpecifications
- Publisher
- Allen AI
- Family
- Tmax
- Parameters
- 9.0B
- Architecture
- Qwen3_5ForConditionalGeneration
- Context Length
- 262,144 tokens
- Vocabulary Size
- 248,320
- Release Date
- 2026-06-17
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Tmax 9B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 4.4 GB | 38.5 GB | 3.81 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 4.5 GB | 38.6 GB | 3.92 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 4.9 GB | 39.0 GB | 4.36 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 5.0 GB | 39.1 GB | 4.48 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 5.9 GB | 40.0 GB | 5.37 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 7.0 GB | 41.0 GB | 6.38 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 8.0 GB | 42.0 GB | 7.39 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 9.5 GB | 43.6 GB | 8.95 GB | 8-bit quantization, near-lossless |
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 Tmax 9B?
Q4_K_M · 5.9 GBTmax 9B (Q4_K_M) requires 5.9 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 8+ GB is recommended. Using the full 262K context window can add up to 34.1 GB, bringing total usage to 40.0 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3070 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Tmax 9B?
Q4_K_M · 5.9 GB58 devices with unified memory can run Tmax 9B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomWhere to Download Tmax 9B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
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Frequently Asked Questions
- How much VRAM does Tmax 9B need?
Tmax 9B requires 5.9 GB of VRAM at Q4_K_M, or 18.5 GB at BF16. Full 262K context adds up to 34.1 GB (40.0 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 9.0B × 4.8 bits ÷ 8 = 5.4 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 34.6 GB (at full 262K context)
VRAM usage by quantization
Q4_K_M5.9 GBQ4_K_M + full context40.0 GB- What's the best quantization for Tmax 9B?
For Tmax 9B, Q4_K_M (5.9 GB) offers the best balance of quality and VRAM usage. Q5_0 (6.2 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 4.4 GB.
VRAM requirement by quantization
Q2_K4.4 GBQ4_05.0 GBQ4_K_S5.6 GBQ4_K_M ★5.9 GBQ5_K_S6.7 GBBF1618.5 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Tmax 9B on a Mac?
Tmax 9B requires at least 4.4 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 Tmax 9B locally?
Yes — Tmax 9B can run locally on consumer hardware. At Q4_K_M quantization it needs 5.9 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Tmax 9B?
At Q4_K_M, Tmax 9B can reach ~741 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~110 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 ÷ 5.9 × 0.65 = ~875 tok/s
Estimated speed at Q4_K_M (5.9 GB)
~875 tok/s~110 tok/s~875 tok/s~741 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Tmax 9B?
At Q4_K_M, the download is about 5.37 GB. The full-precision BF16 version is 17.91 GB. The smallest option (Q2_K) is 3.81 GB.
- Which GPUs can run Tmax 9B?
50 consumer GPUs can run Tmax 9B at Q4_K_M (5.9 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 39 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Tmax 9B?
59 devices with unified memory can run Tmax 9B at Q4_K_M (5.9 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, 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.