Compare/Command-R (Mar '24) vs GPT-3.5 Turbo

Command-R (Mar '24)vsGPT-3.5 Turbo

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-3.5 Turbo

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

Winner by Category

Cheaper
Tie
Faster (tok/s)
Lower Latency
Benchmarks (0-2)
GPT-3.5 Turbo

Pricing Comparison

MetricCommand-R (Mar '24)GPT-3.5 Turbo
Input ($/M tokens)$0.5$0.5
Output ($/M tokens)$1.5$1.5
Cost for 1M input + 100K output tokens:
Command-R (Mar '24)$0.65
GPT-3.5 Turbo$0.65

Speed Comparison

Speed data not available for these models.

Editorial Analysis

Verdict. GPT-3.5 Turbo 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 1.0× the per-million-token cost, GPT-3.5 Turbo is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). GPT-3.5 Turbo 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-3.5 Turbo leads on Coding Index (10.7), Intelligence Index (3.2).

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-3.5 Turbo costs $37.50 ($450/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Command-R (Mar '24) ≈ $5.50/run, GPT-3.5 Turbo ≈ $5.50/run. At agent/realtime scale (200M input / 100M output per million requests): Command-R (Mar '24) ≈ $250/run, GPT-3.5 Turbo ≈ $250/run.

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
1.73.2
Coding Index
10.7
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-3.5 Turbo

Frequently Asked Questions

Which is cheaper, Command-R (Mar '24) or GPT-3.5 Turbo?

Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.

Which model performs better on benchmarks?

GPT-3.5 Turbo 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?

Both models have comparable generation speeds.

When should I use Command-R (Mar '24) vs GPT-3.5 Turbo?

Choose based on your priorities: both are similarly priced, GPT-3.5 Turbo for stronger benchmark performance, and both have comparable speed. For latency-sensitive apps, check the TTFT comparison above.