// head_to_head
Command R+ (08-2024) vs Gemini 4 Argon
Published LiveBench scores across all seven categories, live list pricing, context windows, and the measured cost of a point of capability — for both models, side by side.
Command R+ (08-2024) and Gemini 4 Argon are priced within ~10% of each other.
Command R+ (08-2024) does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.
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Command R+ (08-2024)
- Blended / 1M
- $4.38
- Context
- 128K
- Released
- Aug 30, 2024
- Overall score
- Not evaluated
Gemini 4 Argon
- Blended / 1M
- $4.00
- Context
- 1.0M
- Released
- Oct 13, 2026
- Overall score
- 79.3
Specs and pricing
| Metric | Command R+ (08-2024) | Gemini 4 Argon |
|---|---|---|
| LiveBench overall Weighted mean of the seven LiveBench category scores, 0–100. Higher is better. | — | 79.3 |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | — | $0.0207 |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $4.38 | $4.00 |
| Input price / 1M | $2.50 | $2.00win |
| Output price / 1M | $10.00 | $10.00 |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | — | $0.100 |
| Context window | 128K | 1.0Mwin |
| Max output tokens | 4K | 944Kwin |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Command R+ (08-2024) on top, Gemini 4 Argon below, both out of 100.
What each one costs to run
Per-token prices are hard to feel. These are monthly list costs for both models across five workload shapes, using each provider's published cached-input rate where there is one.
| Workload | Command R+ (08-2024) | Gemini 4 Argon |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $1,400/mo | $1,143/mo |
| RAG assistant 8K in / 600 out × 100K requests | $2,600/mo | $1,440/mo |
| Coding agent 40K in / 4K out × 20K requests | $2,800/mo | $1,336/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $3,250/mo | $2,655/mo |
| Bulk classification 500 in / 20 out × 5M requests | $7,250/mo | $5,050/mo |
Which should you pick?
You need to fit large documents in one call
Gemini 4 Argon
Wider context window — 1.0M against 128K.
Command R+ (08-2024) vs Gemini 4 Argon FAQ
Which is better, Command R+ (08-2024) or Gemini 4 Argon?
Command R+ (08-2024) and Gemini 4 Argon are priced within ~10% of each other. Command R+ (08-2024) does not have a published LiveBench run, so this comparison covers price, context and declared capabilities only. A missing score means "not evaluated", not "worse" — the right way to separate these two is an eval on your own workload.
Is Command R+ (08-2024) cheaper than Gemini 4 Argon?
They cost about the same. Both land near $4.38 per million tokens on a 3:1 input:output blend, so price is unlikely to be the deciding factor between them.
Does Command R+ (08-2024) or Gemini 4 Argon have a bigger context window?
Gemini 4 Argon has the larger context window: 128K for Command R+ (08-2024) against 1.0M for Gemini 4 Argon. Note that a window you can fill is not a window you should fill — retrieval quality usually degrades well before the limit, and you pay for every token you put in it.
Do Command R+ (08-2024) and Gemini 4 Argon support prompt caching?
Gemini 4 Argon publishes a cached-input rate of $0.100 per million tokens against a full input rate of $2.00. The catalogue lists no separate cached rate for Command R+ (08-2024), which means the provider does not price it separately here — not that caching is unavailable.
Related comparisons
How these numbers are produced
- Price — provider list price from OpenRouter, refreshed every 15 minutes. “Blended” is a 3:1 input:output mix.
- Scores — LiveBench release 2026-10-25, using their own category map. Each model shows its strongest published run. A blank means “not evaluated”, never “bad”.
- Cost per point — the measured dollars LiveBench spent on the run, divided by the score it earned.
- “Win” — awarded only past a threshold: one full point on a benchmark score, 10% on a price, 25% on a context window. Anything tighter reports as a tie, because effort settings alone move a LiveBench score by more than that.
Published benchmarks rank models on someone else's tasks. Before committing, see LLM & agent evaluation for building an eval on your own.