Compare/Command-R (Mar '24) vs Gemini 3.1 Flash-Lite

Command-R (Mar '24)vsGemini 3.1 Flash-Lite

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
Google

Gemini 3.1 Flash-Lite

Input
$0.25/M
Output
$1.5/M
Speed
346 tok/s
TTFT
5.64s

Winner by Category

Cheaper
Gemini 3.1 Flash-Lite
Faster (tok/s)
Gemini 3.1 Flash-Lite
Lower Latency
Gemini 3.1 Flash-Lite
Benchmarks (0-2)
Gemini 3.1 Flash-Lite

Pricing Comparison

MetricCommand-R (Mar '24)Gemini 3.1 Flash-Lite
Input ($/M tokens)$0.5$0.25
Output ($/M tokens)$1.5$1.5
Cost for 1M input + 100K output tokens:
Command-R (Mar '24)$0.65
Gemini 3.1 Flash-Lite$0.40

Speed Comparison

Output Speed (tokens/s) — higher is better
Command-R (Mar '24)
Gemini 3.1 Flash-Lite
346 tok/s
Time to First Token (seconds) — lower is better
Command-R (Mar '24)
Gemini 3.1 Flash-Lite
5.64s

Editorial Analysis

Verdict. Gemini 3.1 Flash-Lite 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, Gemini 3.1 Flash-Lite is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Gemini 3.1 Flash-Lite 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). Gemini 3.1 Flash-Lite leads on Coding Index (34.7), Intelligence Index (25.6).

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

Provider. Cohere and Google sell to overlapping but distinct developer audiences: Cohere tends to ship frontier reasoning models with premium positioning, while Google 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); Gemini 3.1 Flash-Lite costs $30.00 ($360/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Command-R (Mar '24) ≈ $5.50/run, Gemini 3.1 Flash-Lite ≈ $4.25/run. At agent/realtime scale (200M input / 100M output per million requests): Command-R (Mar '24) ≈ $250/run, Gemini 3.1 Flash-Lite ≈ $200/run. Gemini 3.1 Flash-Lite 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
1.725.6
Coding Index
34.7
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 winsGemini 3.1 Flash-Lite

Frequently Asked Questions

Which is cheaper, Command-R (Mar '24) or Gemini 3.1 Flash-Lite?

Gemini 3.1 Flash-Lite is cheaper overall. Its blended price (3:1 input/output ratio) is $0.56/M tokens vs $0.75/M for Command-R (Mar '24).

Which model performs better on benchmarks?

Gemini 3.1 Flash-Lite 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?

Gemini 3.1 Flash-Lite generates tokens faster at 346 tok/s vs — tok/s. However, Gemini 3.1 Flash-Lite has lower time-to-first-token (5.64s vs —s).

When should I use Command-R (Mar '24) vs Gemini 3.1 Flash-Lite?

Choose based on your priorities: Gemini 3.1 Flash-Lite for lower cost, Gemini 3.1 Flash-Lite for stronger benchmark performance, and Gemini 3.1 Flash-Lite for faster generation. For latency-sensitive apps, check the TTFT comparison above.