// head_to_head
Command R7B (12-2024) vs DeepSeek V4 Flash 0423
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 R7B (12-2024) is the cheaper of the two; neither can be ranked on quality here.
Command R7B (12-2024) 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.
cohere
Command R7B (12-2024)
- Blended / 1M
- $0.066
- Context
- 128K
- Released
- Dec 14, 2024
- Overall score
- Not evaluated
deepseek
DeepSeek V4 Flash 0423
- Blended / 1M
- $0.111
- Context
- 1.0M
- Released
- Apr 24, 2026
- Overall score
- 65.5
Specs and pricing
| Metric | Command R7B (12-2024) | DeepSeek V4 Flash 0423 |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | — | 65.5 |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | — | $0.0083 |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $0.066win | $0.111 |
| Input price / 1M | $0.037win | $0.089 |
| Output price / 1M | $0.150win | $0.177 |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | — | $0.018 |
| Context window | 128K | 1.0Mwin |
| Max output tokens | 4K | 384Kwin |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Command R7B (12-2024) on top, DeepSeek V4 Flash 0423 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 R7B (12-2024) | DeepSeek V4 Flash 0423 |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $21.00/mo | $30.34/mo |
| RAG assistant 8K in / 600 out × 100K requests | $39.00/mo | $53.16/mo |
| Coding agent 40K in / 4K out × 20K requests | $42.00/mo | $45.37/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $48.75/mo | $98.35/mo |
| Bulk classification 500 in / 20 out × 5M requests | $108.75/mo | $203.79/mo |
Which should you pick?
You need to fit large documents in one call
DeepSeek V4 Flash 0423
Wider context window — 1.0M against 128K.
You are cost-constrained
Command R7B (12-2024)
Cheaper on blended list price at $0.066 per million tokens.
Command R7B (12-2024) vs DeepSeek V4 Flash 0423 FAQ
Which is better, Command R7B (12-2024) or DeepSeek V4 Flash 0423?
Command R7B (12-2024) is the cheaper of the two; neither can be ranked on quality here. Command R7B (12-2024) 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 R7B (12-2024) cheaper than DeepSeek V4 Flash 0423?
Command R7B (12-2024) is cheaper. On a 3:1 input:output blend, Command R7B (12-2024) lists at $0.066 per million tokens and DeepSeek V4 Flash 0423 at $0.111 — Command R7B (12-2024) is 1.7× cheaper. Input and output are priced separately — Command R7B (12-2024) charges $0.037 in and $0.150 out, DeepSeek V4 Flash 0423 charges $0.089 and $0.177 — so the model that looks cheaper flips depending on how output-heavy your workload is.
Does Command R7B (12-2024) or DeepSeek V4 Flash 0423 have a bigger context window?
DeepSeek V4 Flash 0423 has the larger context window: 128K for Command R7B (12-2024) against 1.0M for DeepSeek V4 Flash 0423. 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 R7B (12-2024) and DeepSeek V4 Flash 0423 support prompt caching?
DeepSeek V4 Flash 0423 publishes a cached-input rate of $0.018 per million tokens against a full input rate of $0.089. The catalogue lists no separate cached rate for Command R7B (12-2024), 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 2026-06-25, 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.