What is the biggest model the Tesla M40 can run?

Qwen3 32B, which needs about 22 GB, on the 24 GB version at about 8 tok/s.

What is the biggest model the RX 7600 XT can run?

gpt-oss 20B, which needs about 16 GB, on the 16 GB version at about 50 tok/s.

Tesla M40 vs RX 7600 XT for local AI

Q: Which is better for local AI, the Tesla M40 or the RX 7600 XT?

The Tesla M40: it fits bigger models and runs faster. The Tesla M40 fits more: up to Qwen3 32B, against gpt-oss 20B on the RX 7600 XT. They generate at about the same speed, since their memory bandwidth is close (288 and 288 GB/s).

The Tesla M40 fits more: up to Qwen3 32B, against gpt-oss 20B on the RX 7600 XT. They generate at about the same speed, since their memory bandwidth is close (288 and 288 GB/s).

The numbers that matter

Memory and bandwidth

Memory decides which models fit. Bandwidth decides how fast they generate, because every token reads the model's active weights once.

	Tesla M40	RX 7600 XT
Memory	12 or 24 GB VRAM	16 GB VRAM
Bandwidth	288 GB/s	288 GB/s
Biggest model that fits	Qwen3 32B	gpt-oss 20B
Best everyday pick	Qwen3 30B-A3B, ~50 tok/s	gpt-oss 20B, ~50 tok/s

Model by model

Every model, side by side

Estimated generation speed at the largest memory size each was sold in (24 GB and 16 GB).

Model	Tesla M40	RX 7600 XT
Qwen3 4B About 4 GB	~63 tok/s Runs great	~63 tok/s Runs great
Qwen3 8B About 7 GB	~30 tok/s Runs great	~30 tok/s Runs great
Gemma 3 12B About 10 GB	~20 tok/s Usable	~20 tok/s Usable
Qwen3 14B About 11 GB	~17 tok/s Usable	~17 tok/s Usable
gpt-oss 20B About 16 GB	~50 tok/s Runs great	~50 tok/s Runs great
Gemma 3 27B About 19 GB	~9 tok/s Slow	Needs 19 GB
Qwen3 30B-A3B About 21 GB	~50 tok/s Runs great	Needs 21 GB
Qwen3 32B About 22 GB	~8 tok/s Slow	Needs 22 GB
Llama 3.3 70B About 45 GB	Needs 45 GB	Needs 45 GB
gpt-oss 120B About 67 GB	Needs 67 GB	Needs 67 GB
Qwen3 235B-A22B About 144 GB	Needs 144 GB	Needs 144 GB
DeepSeek R1 671B About 406 GB	Needs 406 GB	Needs 406 GB

Which should you get?

The Tesla M40: it fits bigger models and runs faster. Price matters as much as either number: check used prices on the builds page, where every parts list has a measured or estimated speed.

How we estimate

Both columns use the same formula: memory bandwidth divided by the weights read per token, calibrated on our own rack, with Ollama's default 4-bit sizes. Real results are usually within about a third. Measured either one? Send us the number.

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Other matchups

Every comparison