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Measurement sources and verification status (12 fields)

Collected third-party figures are not independent tests. A source link and collection date do not establish reproducibility. Exact model version, dataset and test settings may be missing. No independent verification date is supplied.

speed: 80

latency: 0.55

contextWindow: 128000

inputPrice: 2.5

outputPrice: 10

benchmarkMmlu: 75.7

benchmarkHumanEval: 75

benchmarkMath: 62

benchmarkGpqa: 30

reasoningScore: 50

codingScore: 75

benchmarkSweBench: 29

Cohere: Command R+ (08-2024)

cohere🔒 Proprietary

command-r-plus-08-2024 is an update of the [Command R+](/models/cohere/command-r-plus) with roughly 50% higher throughput and 25% lower latencies as compared to the previous Command R+ version, while keeping the hardware footprint...

LLM Stats Scores

50.0

Reasoning

75.0

Coding

🎯

30.0%GPQA Diamond — graduate-level science accuracy

Published benchmark evidence

Task scores are reported independently by each publisher; they are not combined into a hidden quality score.

29.0%

SWE-bench

Quality Score

63.0

Overall (0–100)

Speed

80 c/s

characters/second

Latency (TTFT)

0.55s

to first token

Input Price

$2.5

per 1M tokens

Output Price

$10

per 1M tokens

Context Window

128K

tokens

Release Date

2024-08-30

30-Day Rank History

📊 Benchmark Scores

Reported scores · % accuracy

What do these benchmarks test?

🎯

GPQA Diamond30.0%Below avg

Designed so that even PhD-level human experts average ~65–70%. A score above 80% signals near-expert scientific reasoning that goes far beyond memorisation.

🧠

MMLU75.7%Solid

The classic academic breadth benchmark. Top frontier models now score above 85%, so it best distinguishes mid-tier from strong generalist models.

💻

HumanEval75.0%Solid

Measures whether a model writes functionally correct code — not just plausible-looking syntax. Strong scores (>85%) indicate reliable day-to-day coding assistance.

∑

MATH Benchmark62.0%Solid

Tests multi-step mathematical reasoning under strict correctness. Even a 60% score requires strong chain-of-thought; top reasoning models now exceed 90%.