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DeepSeek V3.1

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Open-weights frontier model that matched GPT-4-class quality at a fraction of the inference cost. Sparked the late-2024 cost reset.

DeepSeek V3.1 is a efficient AI model from DeepSeek. It costs $0.250 per million input tokens and $0.950 per million output tokens (blended $0.460/M), with a 163,840-token context window.

Profile inherited from upstream DeepSeek-V3 ↗ — this is a hosted variant of the same open-weights model.

INPUT
$0.250/M
per million input tokens
OUTPUT
$0.950/M
per million output tokens
BLENDED 70/30
$0.460/M
unchanged since 3 May
CONTEXT
163,840
tokens
What it is good at
  • Frontier quality, open weights
  • Aggressive pricing
  • Strong code & math
  • MoE architecture
Typical use cases
  • Self-hosted frontier inference
  • Cost-sensitive chat
  • Code generation

Benchmarks

vs. best public score
Scores inherited from DeepSeek-V3 — this is a hosted variant of the same open-weights model, so the underlying benchmark scores are identical.
MMLU88%
Multitask academic knowledge across 57 subjects.
Graduate-level science questions, "Google-proof".
MATH90%
High-school competition math problems.
Python function synthesis from docstrings.
Real GitHub issues solved end-to-end.
LMArena Elo1318 Elo
Crowd-sourced head-to-head preference Elo rating.
Hand-curated from each provider's published reports and public leaderboards. Methodology varies across sources, treat as directional rather than authoritative.

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Frequently asked questions

How much does DeepSeek V3.1 cost?

DeepSeek V3.1 costs $0.250 per million input tokens and $0.950 per million output tokens, for a blended reference rate of $0.460 per million tokens.

What is DeepSeek V3.1's context window?

DeepSeek V3.1 supports up to 163,840 tokens of context in a single request.

What is DeepSeek V3.1 best for?

DeepSeek V3.1 is well suited to Frontier quality, open weights, Aggressive pricing and Strong code & math.

Who makes DeepSeek V3.1?

DeepSeek V3.1 is developed and served by DeepSeek.

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