// head_to_head
GPT-6 Luna vs Jev Router
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.
GPT-6 Luna and Jev Router are priced within ~10% of each other.
Jev Router 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.
openai
GPT-6 Luna
- Blended / 1M
- $0.200
- Context
- 1.1M
- Released
- Sep 22, 2026
- Overall score
- 72.0
typesafe
Jev Router
- Blended / 1M
- —
- Context
- 1M
- Released
- Sep 25, 2026
- Overall score
- Not evaluated
Specs and pricing
| Metric | GPT-6 Luna | Jev Router |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | 72.0 | — |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.0134 | — |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $0.200 | — |
| Input price / 1M | $0.100 | — |
| Output price / 1M | $0.500 | — |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $0.010 | — |
| Context window | 1.1M | 1M |
| Max output tokens | 128K | — |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — GPT-6 Luna on top, Jev Router 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.
Run these two through the cost calculatorGPT-6 Luna vs Jev Router FAQ
Which is better, GPT-6 Luna or Jev Router?
GPT-6 Luna and Jev Router are priced within ~10% of each other. Jev Router 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.
Does GPT-6 Luna or Jev Router have a bigger context window?
They are effectively the same — 1.1M for GPT-6 Luna and 1M for Jev Router.
Do GPT-6 Luna and Jev Router support prompt caching?
GPT-6 Luna publishes a cached-input rate of $0.010 per million tokens against a full input rate of $0.100. The catalogue lists no separate cached rate for Jev Router, 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.