Model profile
Cohere

Command-R+ (Apr '24)

Command-R+ (Apr '24) is a mid-range-priced text-first model from Cohere with partial runtime data, partial context coverage, and the clearest fit around coding / reasoning.

Best for: Coding / ReasoningN/A latencyN/A contextMid-range pricing
Intelligence
8.3

Benchmark blend

Coding
0.122

Dev workflow signal

Context
N/A

N/A

Input Price
$3.00

Mid-range tier

Decision snapshot
22

Command-R+ (Apr '24) currently reads as a mid-range text-first option with partially published context and a partially published runtime profile.

Overall profile
Use-case specific
Best for
Coding / Reasoning
Latency tier
N/A
Price tier
Mid-range
Source coverage
OpenRouterArtificial Analysis

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
8.3
8

General reasoning and benchmark headroom.

Limited
Speed
N/A
N/A

Latency data is partial.

Unavailable
Context
N/A
N/A

How much prompt and task state can stay in view.

Unavailable
Price
$3.00
62

$15.00 output / 1M

Competitive

Editorial Profile

Command-R+ (Apr '24) in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Use-case specificCoding score 12Math score 28

The Command-R+ (Apr '24) AI model by Cohere.

Identity

Cohere text-first profile

Positioning

Coding / Reasoning with partially published context and partially published runtime.

Cost posture

Balanced spend profile. Easier to justify in mixed production and exploration workloads.

Strengths
  • The available source data suggests a balanced profile rather than one dominant edge.

Tradeoffs
  • Costs look manageable, but still deserve attention in always-on agents or batch jobs.

  • Latency data is incomplete, so interactive responsiveness is harder to rank confidently.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

  • Context limits are only partially published, so long-session planning needs extra validation.

Best fit
  • Focused chat, retrieval-augmented flows, and narrower production tasks.

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Context
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Input Price
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Context
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Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
8.3
MMLU Pro
43.2%
GPQA
32.3%
HLE
4.5%
Coding

Software implementation, debugging quality, and coding benchmark signal.

LiveCodeBench
0.122
SciCode
11.8%
Math

Formal reasoning, structured problem solving, and competition-style math.

AIME
0.7%
Math 500
27.9%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
N/A
Vision
Text-first
Price architecture
Input
per 1M input tokens
$3.00
Output
per 1M output tokens
$15.00
Blended
AA 3:1 mix
$6.00

This model sits in a balanced spend range. It is easier to justify across both production and exploratory workflows.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.