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Run LLM Locally

Qwen3 1.7B on the Tesla P40

With 24 GB of VRAM, the Tesla P40 runs Qwen3 1.7B at Q4_K_M entirely on the GPU with an 8K context (about 3.1 GB needed). At Q8_0 it fits entirely.

Qwen3 1.7B

Q4_K_M · 8K context

Excellent

The model needs about 3.1 GB and fits in the 23.3 GB available, with 20.1 GB to spare.

Your hardware
Tesla P40 24 GB · 64 GB RAM
Estimated memory
~3.1 GB estimate
VRAM (usable memory)
23.3 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
121–176 tok/s estimate
Largest context in fast memory
32K tokens
Confidence: low

Based on: memory bandwidth (346 GB/s) and model size

Memory breakdown

~3.1 GB (2.8 GB–3.5 GB) needed · estimate

Fits entirely in VRAM · 20.1 GB left

  • Model weights1.2 GB
  • KV cache0.9 GB
  • Runtime overhead0.8 GB
  • Safety margin0.3 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (CUDA) · flash attention on · weights = real file size

EstimateData updated 24 days agoSource: Run LLM Locally engine, Hugging Face config.json + model card

What makes this estimate less reliable

  • no benchmark for this hardware and model yet

Other quantizations on the Tesla P40

Qwen3 1.7B on Tesla P40 + 64 GB RAM · 8K context
Qwen3 1.7B Q8_08K~3.7 GB · 97–137 tok/s estimateExcellent
Qwen3 1.7B Q6_K8K~3.5 GB · 103–146 tok/s estimateExcellent
Qwen3 1.7B Q5_K_M8K~3.3 GB · 112–160 tok/s estimateExcellent
Qwen3 1.7B Q4_K_M8K~3.1 GB · 121–176 tok/s estimateExcellent
Qwen3 1.7B IQ4_XS8K~3 GB · 128–186 tok/s estimateExcellent
Qwen3 1.7B Q3_K_M8K~2.9 GB · 134–197 tok/s estimateExcellent

Alternatives

Hardware that runs Qwen3 1.7B Q4_K_M entirely in memory

Prices and links follow the market you choose.

GeForce RTX 4060

NVIDIA

ExcellentRuns Qwen3 1.7B Q4_K_M entirely in memory

Price not available

Availability unknown

View on amazon.com

Affiliate link

Radeon RX 7600 XT

AMD

ExcellentRuns Qwen3 1.7B Q4_K_M entirely in memory

Price not available

Availability unknown

View on amazon.com

Affiliate link

AMD Ryzen AI Max+ 395

Unified memory PC

ExcellentRuns Qwen3 1.7B Q4_K_M entirely in memory

Price not available

Availability unknown

View on amazon.com

Affiliate link

No current offer imported for this market: the link opens a marketplace search.

Frequently asked questions

Can the Tesla P40 run Qwen3 1.7B?
The model needs about 3.1 GB and fits in the 23.3 GB available, with 20.1 GB to spare.
Which quantization should I use on the Tesla P40?
Q8_0 is the highest-precision quantization that fits entirely in VRAM at 8K context. ~3.7 GB / 23.3 GB.
What is the largest context on the Tesla P40?
At Q4_K_M, about 32K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is Qwen3 1.7B (Tesla P40)?
We estimate 121–176 tok/s (estimate, confidence low). Based on: memory bandwidth (346 GB/s) and model size.