Cohereproprietary
Released: 2024-04-04

Command R+

Cohere 104B enterprise-grade model optimized for multi-step retrieval-augmented generation (RAG) and tool use.

Intelligence Index
74.0/ 100
Calibrated multi-domain composite
Throughput Speed
50tok/sec
Output streaming throughput
Time To First Token
480ms
Initial chunk server latency
LiveBench Contam-Free
—%
September 2026 suite score

Sourced Benchmark Evaluations (22)

Verified performance across authoritative benchmarks with provenance tracking.
BenchmarkStatusScoreTrustDateSource TypeProvenance
StructFlowBenchNearing Saturation57.9%
75
2024-04-22independentSource ↗
FireBenchActive57.2%
95
2024-04-20independentSource ↗
SimpleQAActive38.5%
90
2024-04-19independentSource ↗
OpenAI-MRCRActive62.2%
80
2024-04-19independentSource ↗
ComplexBenchNearing Saturation55.8%
80
2024-04-18independentSource ↗
LongBench-ProActive60.7%
80
2024-04-18independentSource ↗
ZeroSCROLLSNearing Saturation59.2%
78
2024-04-17independentSource ↗
InfiniteBenchNearing Saturation62.9%
65
2024-04-16independentSource ↗
AgentIFNearing Saturation46.3%
80
2024-04-16independentSource ↗
MMLU-ProNearing Saturation68.1%
75
2024-04-15independentSource ↗
SCROLLSNearing Saturation59.2%
65
2024-04-15independentSource ↗
RULERNearing Saturation68.1%
84
2024-04-14independentSource ↗
MMLU-ReduxSaturated72.5%
25
2024-04-13independentSource ↗
QuALITYNearing Saturation65.1%
78
2024-04-13independentSource ↗
LongBenchNearing Saturation63.6%
65
2024-04-12independentSource ↗
QASPERNearing Saturation61.4%
65
2024-04-11independentSource ↗
TruthfulQASaturated65.1%
25
2024-04-11independentSource ↗
MT-BenchNearing Saturation7%
75
2024-04-09independentSource ↗
IFEvalDeprecated66.7%
25
2024-04-08independentSource ↗
GPQANearing Saturation65.1%
78
2024-04-08independentSource ↗
Needle-in-a-HaystackSaturated94.8%
44
2024-04-07independentSource ↗
MMLUSaturated75.5%
25
2024-04-05independentSource ↗
OpenAI Compatible API ExecutionAPI Ready
from openai import OpenAI

client = OpenAI()
response = client.chat.completions.create(
    model="command-r-plus",
    messages=[{"role": "user", "content": "Evaluate multi-step logic problem"}],
    temperature=0.2
)
print(response.choices[0].message.content)

Evaluation & Sourcing Notes

Scores listed for Command R+ represent verified evaluations extracted from official research papers, independent evaluation suites (HELM, LMSYS, OpenCompass, LiveBench), and verified audit reports.

All benchmarks marked as saturated or deprecated reflect historical performance where the benchmark no longer provides active discriminative power.