How much VRAM does Devstral Small 2 24B need?

48 GB for its weights at 16-bit, 24 GB at 8-bit and 13.5 GB at 4-bit, plus the KV cache: 164 KB for each token, 5.37 GB for a conversation of 32K tokens and 64.4 GB at its longest context of 393,216 tokens. The server also keeps about 8% of each GPU free.

Can Devstral Small 2 24B run on 1 GPU?

Yes, at 4-bit: the smallest single GPU here that holds it with a 32K conversation is the L4.

How many H100s does Devstral Small 2 24B need?

With 1 conversation of 32K tokens, 1 H100 at 16-bit and 1 H100 at 4-bit. Each H100 has 80 GB, of which vLLM uses 92% by default.

Can I run Devstral Small 2 24B on an RTX 5090?

The RTX 5090 has 32 GB. With a 32K conversation, Devstral Small 2 24B needs 1 GeForce RTX 5090 at 4-bit and 2 GeForce RTX 5090s at 16-bit.

How fast does Devstral Small 2 24B run?

At 4-bit on 1 H100, memory lets 1 conversation get at most 177 tokens a second. Real servers reach part of that ceiling, and each conversation gets less when many run at once.

How much GPU memory does Devstral Small 2 24B need?

Devstral Small 2 24B by Mistral AI has 24B parameters. Its weights take 48 GB at 16-bit, 24 GB at 8-bit and 13.5 GB at 4-bit; released in FP8, its files are 25.8 GB. Each token of a conversation adds 164 KB of KV cache, so a 32K conversation holds 5.37 GB.

Size Devstral Small 2 24B for your setup Questions

Mistral AI · released in FP8

Devstral Small 2 24B at a glance

Parameters: 24B
As released: 25.8 GB; Its FP8 files
At 16-bit: 48 GB
At 4-bit: 13.5 GB; NVFP4
KV cache a token: 164 KB; At 16-bit
Longest context: 393,216; Tokens

GPUs needed at each number format

For 1 conversation of 32,768 tokens with a 16-bit KV cache, counting 92% of each GPU's memory as vLLM does. Under each count, the most tokens a second memory allows.

GPU	Memory	16-bit	8-bit	4-bit
L4	24 GB	4 GPUs22 tokens/s	2 GPUs20 tokens/s	1 GPU16 tokens/s
GeForce RTX 5090	32 GB	2 GPUs67 tokens/s	1 GPU61 tokens/s	1 GPU95 tokens/s
L40S	48 GB	2 GPUs32 tokens/s	1 GPU29 tokens/s	1 GPU46 tokens/s
A100 80GB	80 GB	1 GPU38 tokens/s	1 GPU69 tokens/s	1 GPU108 tokens/s
H100	80 GB	1 GPU63 tokens/s	1 GPU114 tokens/s	1 GPU177 tokens/s
RTX PRO 6000 Blackwell	96 GB	1 GPU34 tokens/s	1 GPU61 tokens/s	1 GPU95 tokens/s
DGX Spark	128 GB	1 GPU5.1 tokens/s	1 GPU9.3 tokens/s	1 GPU14 tokens/s
H200	141 GB	1 GPU90 tokens/s	1 GPU163 tokens/s	1 GPU254 tokens/s
B200	180 GB	1 GPU150 tokens/s	1 GPU272 tokens/s	1 GPU424 tokens/s
Instinct MI300X	192 GB	1 GPU99 tokens/s	1 GPU180 tokens/s	1 GPU281 tokens/s
Instinct MI325X	256 GB	1 GPU112 tokens/s	1 GPU204 tokens/s	1 GPU318 tokens/s
Instinct MI355X	288 GB	1 GPU150 tokens/s	1 GPU272 tokens/s	1 GPU424 tokens/s

Models of a similar size

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Questions

How much VRAM does Devstral Small 2 24B need?: 48 GB for its weights at 16-bit, 24 GB at 8-bit and 13.5 GB at 4-bit, plus the KV cache: 164 KB for each token, 5.37 GB for a conversation of 32K tokens and 64.4 GB at its longest context of 393,216 tokens. The server also keeps about 8% of each GPU free.
Can Devstral Small 2 24B run on 1 GPU?: Yes, at 4-bit: the smallest single GPU here that holds it with a 32K conversation is the L4.
How many H100s does Devstral Small 2 24B need?: With 1 conversation of 32K tokens, 1 H100 at 16-bit and 1 H100 at 4-bit. Each H100 has 80 GB, of which vLLM uses 92% by default.
Can I run Devstral Small 2 24B on an RTX 5090?: The RTX 5090 has 32 GB. With a 32K conversation, Devstral Small 2 24B needs 1 GeForce RTX 5090 at 4-bit and 2 GeForce RTX 5090s at 16-bit.
How fast does Devstral Small 2 24B run?: At 4-bit on 1 H100, memory lets 1 conversation get at most 177 tokens a second. Real servers reach part of that ceiling, and each conversation gets less when many run at once.

Sources

Devstral Small 2 24B at a glance

GPUs needed at each number format

Models of a similar size

Questions

Where each fact comes from