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DeepSeek V3 Turbo

Novita AI's speed-optimized deployment of DeepSeek V3.

Params
671B, 37B active
Context
64K tokens
License
DeepSeek Model License

Estimated cost to self-host

DeepSeek V3 Turbo needs about 373 GB of GPU memory at 4-bit with 32K context. The cheapest rental that fits is 8× A100 at about $10,714 a month.

Single node ≤ 8
What it costs to self-host DeepSeek V3 Turbo at each precision: the memory it needs, the cheapest rental that holds it, that rental's month and the API volume it pays off at
Precision Memory Cheapest fit (32K context) Cost /mo
4-bit INT4 / FP4 373 GB Nvidia logo 8× A100 $10,714
8-bit FP8 / INT8 674 GB Nvidia logo 8× RTX PRO 6000 $13,709
16-bit FP16 / BF16 1,346 GB Nvidia logo 8× B300 $54,720

Estimates based on median on-demand rates for Nvidia GPUs. Memory is weights plus KV cache for one request, using FP8 KV cache where supported and FP16/BF16 otherwise. No guarantee of runtime support, usable performance, or that a matching quantized build exists. Pricing methodology.

Capabilities

What DeepSeek V3 Turbo accepts and can do, as published by DeepSeek.

  • Text Accepts and generates natural-language text.
  • Function calling Connect to external tools, APIs, and systems.

Common questions

What is DeepSeek V3 Turbo good for?

General chat and coding with tool calling, through Novita AI's own build of DeepSeek V3, which it says is tuned for speed.

When is DeepSeek V3 Turbo not a good fit?

Long-context work: its window is shorter than standard V3's. No structured output, and it is text only.

What is the cheapest way to run DeepSeek V3 Turbo?

No provider we track hosts it; self-hosting on the cheapest rental that fits (8x A100, $14.88 per hour) costs about $10,714 a month.

Can I self-host DeepSeek V3 Turbo?

Yes. The weights are released under the DeepSeek Model License. At 4-bit it needs about 373 GB of GPU memory, which starts at roughly $10,714 a month on the cheapest rental that fits.

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