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llmwaves

V3.1

DeepSeek · released Aug 21, 2025

Open weightsReasoningTool useStructured output

DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context...

Specification

Context window
164K
Max output
33K
Knowledge cutoff
Mar 31, 2025
Parameters
684.5B
Licence
mit
Serving providers
8
Moderated
No
Uptime
100.0%

Intelligence

Not benchmarked

Coding

Coding Index

Agentic

Agentic Index

Output speed

63 t/s

Median across providers

Latency

377ms

Time to first token

Cost per task

$0.09

Estimated

Benchmarks

Where the score comes from

The Intelligence Index is a composite. These are the underlying evaluations this model was actually measured on.

Evaluation scores

This model has not been put through the benchmark suite. Its speed, latency and pricing figures below are still measured.

Against its peers

Intelligence Index · this model highlighted, nearest peers in grey

Peers are the models sitting closest on the Intelligence Index — the set you would realistically choose between.

View as table
ModelIntelligence
Claude Opus 563.1
Claude Fable 562.1
GPT-5.6 Sol60.9
Kimi K359.7
Qwen3.8 Max58.1
Claude Opus 4.857.3
Muse Spark 1.256.8

Pricing

What it costs to run

List prices per million tokens, plus what one representative task works out to.

List price

Input / 1M tokens
$0.25
Output / 1M tokens
$0.95
Cached input / 1M
$0.13
Blended 3:1
$0.425

One task, estimated

$0.09

Input tokens
50,000
Output tokens
80,000
Profile
Reasoning

Estimated from list pricing: 50K input tokens plus 80K output tokens for reasoning models (25K for non-reasoning).

Serving providers

Speed and latency figures are medians across these providers, so a widely-served model reports a blend rather than any single endpoint.