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R1

by DeepSeek

DeepSeek R1 is here: Performance on par with OpenAI o1, but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inf

R

Models

R1

Added 10 July 2026

#deepseek

Overview

DeepSeek R1 is here: Performance on par with OpenAI o1, but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....

Best for

Best for
Cost-sensitive reasoning and coding agents

Use cases

  • batch analysis
  • coding assistants on a budget
  • eval baselines

How to use / API access

Call via OpenRouter with model id `deepseek/deepseek-r1`.

  • openrouter · deepseek/deepseek-r1 Docs

OpenRouter id: deepseek/deepseek-r1

Benchmarks

  • Intelligence Index (artificial-analysis): 11.4 index
  • Coding Index (artificial-analysis): 24.6 index
  • Agentic Index (artificial-analysis): 1.1 index

Enterprise DNA angle

Omni lets teams A/B DeepSeek against Sonnet on real jobs with shared eval harnesses.

Notes

R1 is listed in the EDNA Models directory from the OpenRouter catalogue.

Pros

  • Strong reasoning at aggressive price points
  • Good coding signal for the cost
  • Useful open-weight-adjacent economics via OpenRouter

Cons

  • Ecosystem and safety tooling less mature than frontier US labs
  • Quality variance across tasks — eval before production
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USAGE / OPENROUTER

How much R1 is used

Tokens processed through OpenRouter each day. It shows what developers actually run, not every company's private traffic.

Tokens, last 7 days
2B ▲7%
Requests, last 7 days
284K
Tool calls, last 7 days
5.6K
Intelligence score
11.4
People's vote
1373
0250M500M19 Sept: 268M tokens, 36.6K requests20 Sept: 293M tokens, 39.3K requests21 Sept: 361M tokens, 43.6K requests22 Sept: 306M tokens, 90.2K requests23 Sept: 267M tokens, 38.6K requests24 Sept: 247M tokens, 35.1K requests25 Sept: 260M tokens, 36.1K requests26 Sept: 257M tokens, 39.2K requests27 Sept: 266M tokens, 37.5K requests28 Sept: 307M tokens, 47.6K requests29 Sept: 466M tokens, 62.3K requests30 Sept: 230M tokens, 39.8K requests1 Oct: 323M tokens, 42.3K requests2 Oct: 263M tokens, 43.3K requests3 Oct: 237M tokens, 44.1K requests4 Oct: 286M tokens, 47.7K requests5 Oct: 332M tokens, 66.4K requests6 Oct: 308M tokens, 76K requests7 Oct: 315M tokens, 68.6K requests8 Oct: 233M tokens, 33.4K requests9 Oct: 221M tokens, 32.4K requests10 Oct: 210M tokens, 29.8K requests11 Oct: 233M tokens, 34.5K requests12 Oct: 266M tokens, 38.7K requests13 Oct: 250M tokens, 37.9K requests14 Oct: 262M tokens, 38.7K requests15 Oct: 325M tokens, 43.8K requests16 Oct: 342M tokens, 47.5K requests17 Oct: 276M tokens, 43.3K requests18 Oct: 263M tokens, 33.8K requests19 Sept3 Oct17 Oct18 OctSee where it ranks on the leaderboard →

FROM SPECIFICATIONS TO YOUR WORK

Is this the right model for your job?

Start with a realistic sample. These workflows match the model’s listed capabilities, not a verified result on your task.

Check the source

Price date: 2026-10-18. Prices are USD API token rates. Your app subscription, uploads, browsing and tools are separate.

Model source & availability ↗

Understand the evidence

Listed capabilities and third-party benchmark scores do not establish Enterprise DNA task-test results. Validate accuracy and total cost on your own sample.

Intelligence Index: 11.4 (2026-10-18) ↗Coding Index: 24.6 (2026-10-18) ↗Agentic Index: 1.1 (2026-10-18) ↗
Compare this model with alternatives →