Compare/Command-R (Mar '24) vs GPT-4.1 mini

Command-R (Mar '24)vsGPT-4.1 mini

Side-by-side comparison of pricing, 12 benchmarks, and generation speed.

Cohere

Command-R (Mar '24)

Input
$0.5/M
Output
$1.5/M
Speed
TTFT
OpenAI

GPT-4.1 mini

Input
$0.4/M
Output
$1.6/M
Speed
86 tok/s
TTFT
0.84s

Winner by Category

Cheaper
GPT-4.1 mini
Faster (tok/s)
GPT-4.1 mini
Lower Latency
GPT-4.1 mini
Benchmarks (0-2)
GPT-4.1 mini

Pricing Comparison

MetricCommand-R (Mar '24)GPT-4.1 mini
Input ($/M tokens)$0.5$0.4
Output ($/M tokens)$1.5$1.6
Cost for 1M input + 100K output tokens:
Command-R (Mar '24)$0.65
GPT-4.1 mini$0.56

Speed Comparison

Output Speed (tokens/s) — higher is better
Command-R (Mar '24)
GPT-4.1 mini
86 tok/s
Time to First Token (seconds) — lower is better
Command-R (Mar '24)
GPT-4.1 mini
0.84s

Editorial Analysis

Verdict. GPT-4.1 mini takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.

Pricing. Both models sit in the budget bracket for output-token pricing. At 0.9× the per-million-token cost, Command-R (Mar '24) is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Command-R (Mar '24) makes more sense when output volume is low and absolute reasoning quality justifies the premium.

Strengths. Command-R (Mar '24) is strongest on Intelligence Index (1.7). GPT-4.1 mini leads on Coding Index (20.2), Intelligence Index (14.8).

Speed. Speed data is incomplete for this pair; benchmark and price should decide.

Provider. Cohere and OpenAI sell to overlapping but distinct developer audiences: Cohere tends to ship frontier reasoning models with premium positioning, while OpenAI often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.

Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): Command-R (Mar '24) costs $37.50 ($450/year); GPT-4.1 mini costs $36.00 ($432/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Command-R (Mar '24) ≈ $5.50/run, GPT-4.1 mini ≈ $5.20/run. At agent/realtime scale (200M input / 100M output per million requests): Command-R (Mar '24) ≈ $250/run, GPT-4.1 mini ≈ $240/run. GPT-4.1 mini becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.

Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.

Benchmark Comparison

Data from Artificial Analysis API — 12 benchmarks

Intelligence Index
1.714.8
Coding Index
20.2
Math Index
GPQA Diamond
MMLU-Pro
LiveCodeBench
AIME 2025
MATH-500
Humanity's Last Exam
SciCode
IFBench
TerminalBench
Command-R (Mar '24)0 wins
2 winsGPT-4.1 mini

Frequently Asked Questions

Which is cheaper, Command-R (Mar '24) or GPT-4.1 mini?

GPT-4.1 mini is cheaper overall. Its blended price (3:1 input/output ratio) is $0.70/M tokens vs $0.75/M for Command-R (Mar '24).

Which model performs better on benchmarks?

GPT-4.1 mini wins 2 out of 12 benchmarks compared to 0 for Command-R (Mar '24). See the detailed benchmark chart above for per-category results.

Which is faster for real-time applications?

GPT-4.1 mini generates tokens faster at 86 tok/s vs — tok/s. However, GPT-4.1 mini has lower time-to-first-token (0.84s vs —s).

When should I use Command-R (Mar '24) vs GPT-4.1 mini?

Choose based on your priorities: GPT-4.1 mini for lower cost, GPT-4.1 mini for stronger benchmark performance, and GPT-4.1 mini for faster generation. For latency-sensitive apps, check the TTFT comparison above.