// head_to_head
Ox Alpha vs SpaceXAI: Grok 4.6
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.
SpaceXAI: Grok 4.6 scores higher, Ox Alpha costs less — it depends on your workload.
SpaceXAI: Grok 4.6 is ahead by 8.8 points overall, and Ox Alpha lists at a lower blended price. Whether 8.8 points is worth that depends on how much a wrong answer costs you. Ox Alpha also leads on measured cost per point of capability, at $0.0000 per point.
stealth
Ox Alpha
- Blended / 1M
- Free
- Context
- 1.0M
- Released
- Aug 20, 2026
- Overall score
- 69.2
x-ai
SpaceXAI: Grok 4.6
- Blended / 1M
- $3.00
- Context
- 500K
- Released
- Aug 12, 2026
- Overall score
- 78.0
Specs and pricing
| Metric | Ox Alpha | SpaceXAI: Grok 4.6 |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | 69.2 | 78.0win |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.0000win | $0.1181 |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | Freewin | $3.00 |
| Input price / 1M | Freewin | $2.00 |
| Output price / 1M | Freewin | $6.00 |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | — | $0.500 |
| Context window | 1.0Mwin | 500K |
| Max output tokens | 131K | — |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Ox Alpha on top, SpaceXAI: Grok 4.6 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 | Ox Alpha | SpaceXAI: Grok 4.6 |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $0/mo | $852.00/mo |
| RAG assistant 8K in / 600 out × 100K requests | $0/mo | $1360.00/mo |
| Coding agent 40K in / 4K out × 20K requests | $0/mo | $1240.00/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $0/mo | $2375.00/mo |
| Bulk classification 500 in / 20 out × 5M requests | $0/mo | $4850.00/mo |
Which should you pick?
You are running this at volume
Ox Alpha
Lowest measured cost per point of capability at $0.0000 per point — the gap compounds with every request.
Quality matters more than the bill
SpaceXAI: Grok 4.6
Highest overall LiveBench score of the two at 78.0.
The workload is coding or agentic work
SpaceXAI: Grok 4.6
Leads on agentic coding — 57.0 against 52.6.
You need to fit large documents in one call
Ox Alpha
Wider context window — 1.0M against 500K.
Ox Alpha vs SpaceXAI: Grok 4.6 FAQ
Which is better, Ox Alpha or SpaceXAI: Grok 4.6?
SpaceXAI: Grok 4.6 scores higher, Ox Alpha costs less — it depends on your workload. SpaceXAI: Grok 4.6 is ahead by 8.8 points overall, and Ox Alpha lists at a lower blended price. Whether 8.8 points is worth that depends on how much a wrong answer costs you. Ox Alpha also leads on measured cost per point of capability, at $0.0000 per point.
Is Ox Alpha cheaper than SpaceXAI: Grok 4.6?
Ox Alpha is cheaper. On a 3:1 input:output blend, Ox Alpha lists at Free per million tokens and SpaceXAI: Grok 4.6 at $3.00. Input and output are priced separately — Ox Alpha charges Free in and Free out, SpaceXAI: Grok 4.6 charges $2.00 and $6.00 — so the model that looks cheaper flips depending on how output-heavy your workload is.
Ox Alpha vs SpaceXAI: Grok 4.6: which scores higher on benchmarks?
Ox Alpha scores 69.2 and SpaceXAI: Grok 4.6 scores 78.0 overall on LiveBench, the mean of its seven categories. That is a 8.8-point lead for SpaceXAI: Grok 4.6. Category scores differ from the overall figure — a model can lead on reasoning and trail on coding, which the per-category table above breaks out.
Which gives better value for money, Ox Alpha or SpaceXAI: Grok 4.6?
Ox Alpha. Cost per point divides the measured dollars LiveBench spent running the benchmark by the score it earned, so it captures something token pricing misses: a reasoning model can emit many times more tokens than its per-token rate suggests. Ox Alpha works out at $0.0000 per point and SpaceXAI: Grok 4.6 at $0.1181.
Does Ox Alpha or SpaceXAI: Grok 4.6 have a bigger context window?
Ox Alpha has the larger context window: 1.0M for Ox Alpha against 500K for SpaceXAI: Grok 4.6. 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 Ox Alpha and SpaceXAI: Grok 4.6 support prompt caching?
SpaceXAI: Grok 4.6 publishes a cached-input rate of $0.500 per million tokens against a full input rate of $2.00. The catalogue lists no separate cached rate for Ox Alpha, 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.