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DeepSeek Coder 6.7B

by DeepSeek · Released Jan 2024

Open Source
17.1
avg score
Rank #288
Compare
Better than 8% of all models
Context
N/A
Input $/1M
n/a
Output $/1M
n/a
Type
text
License
Open Source
Benchmarks
4 tested
Data as of
About

Tested on 4 benchmarks · BenchGecko score 17.1. Top scores: GSM8K (21.3%), ARC AI2 (15.2%), MMLU (15.2%).

Capabilities
math
21.3
#218 globally
knowledge
15.2
#277 globally
Benchmark Scores
Compare All
Tested on 4 benchmarks · Ranked across 2 categories
Score Distribution (all 312 models)
0255075100
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GSM8K

Grade school math word problems. 8,500 problems testing multi-step arithmetic reasoning. A foundational math benchmark.

21.3·
ARC AI2

AI2 Reasoning Challenge. Grade-school science questions requiring multi-step reasoning. Easy and Challenge sets test different difficulty levels.

15.2·
MMLU

Massive Multitask Language Understanding. 57 subjects from STEM, humanities, and social sciences. The most widely-cited knowledge benchmark.

15.2·
Winogrande

Commonsense coreference resolution. Tests understanding of pronoun references in ambiguous sentences.

15.2·
Excellent (85+) Good (70-85) Average (50-70) Below (<50)
Links
Documentation
Community
BenchGecko API
deepseek-coder-6-7b
Specifications
  • Typetext
  • ContextN/A
  • ReleasedJan 2024
  • LicenseOpen Source
  • Statusbenchmark-only
Available On
DeepSeek logoDeepSeekn/a
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DeepSeek Coder 6.7B is an open-source text AI model by DeepSeek, released in January 2024. It has an average benchmark score of 17.1.

Key facts · as of 2026-04-09

  • DeepSeek Coder 6.7B by DeepSeek. BenchGecko score 17.1, rank 288 of 312 scored models (normalized average of public benchmark scores).
  • List price n/a input · n/a output per 1M tokens (as of 2026-04-09).

How to cite · data as of 2026-04-09

DeepSeek Coder 6.7B · benchmarks, pricing and providers. BenchGecko, data as of 2026-04-09. https://benchgecko.ai/model/deepseek-coder-6-7b

Credit "Source: BenchGecko" with a link. Prices per provider and Gecko Tests are BenchGecko data (CC BY 4.0); benchmark scores keep their original source, listed in the JSON. JSON · llms.txt · MCP