// head_to_head
SpaceXAI: Grok 4.6 vs GLM 5.2
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, GLM 5.2 costs less — it depends on your workload.
SpaceXAI: Grok 4.6 is ahead by 4.9 points overall, and GLM 5.2 lists 2.0× cheaper per blended million tokens. Whether 4.9 points is worth that depends on how much a wrong answer costs you.
x-ai
SpaceXAI: Grok 4.6
- Blended / 1M
- $3.00
- Context
- 500K
- Released
- Aug 12, 2026
- Overall score
- 78.0
z-ai
GLM 5.2
- Blended / 1M
- $1.48
- Context
- 1.0M
- Released
- Jun 16, 2026
- Overall score
- 73.2
Specs and pricing
| Metric | SpaceXAI: Grok 4.6 | GLM 5.2 |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | 78.0win | 73.2 |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $0.1181 | $0.1260 |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $3.00 | $1.48win |
| Input price / 1M | $2.00 | $0.966win |
| Output price / 1M | $6.00 | $3.04win |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $0.500 | $0.193win |
| Context window | 500K | 1.0Mwin |
| 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 — SpaceXAI: Grok 4.6 on top, GLM 5.2 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 | SpaceXAI: Grok 4.6 | GLM 5.2 |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $852.00/mo | $419.08/mo |
| RAG assistant 8K in / 600 out × 100K requests | $1360.00/mo | $645.84/mo |
| Coding agent 40K in / 4K out × 20K requests | $1240.00/mo | $582.91/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $2375.00/mo | $1155.06/mo |
| Bulk classification 500 in / 20 out × 5M requests | $4850.00/mo | $2332.20/mo |
Which should you pick?
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 51.8.
You need to fit large documents in one call
GLM 5.2
Wider context window — 1.0M against 500K.
SpaceXAI: Grok 4.6 vs GLM 5.2 FAQ
Which is better, SpaceXAI: Grok 4.6 or GLM 5.2?
SpaceXAI: Grok 4.6 scores higher, GLM 5.2 costs less — it depends on your workload. SpaceXAI: Grok 4.6 is ahead by 4.9 points overall, and GLM 5.2 lists 2.0× cheaper per blended million tokens. Whether 4.9 points is worth that depends on how much a wrong answer costs you.
Is SpaceXAI: Grok 4.6 cheaper than GLM 5.2?
GLM 5.2 is cheaper. On a 3:1 input:output blend, SpaceXAI: Grok 4.6 lists at $3.00 per million tokens and GLM 5.2 at $1.48 — GLM 5.2 is 2.0× cheaper. Input and output are priced separately — SpaceXAI: Grok 4.6 charges $2.00 in and $6.00 out, GLM 5.2 charges $0.966 and $3.04 — so the model that looks cheaper flips depending on how output-heavy your workload is.
SpaceXAI: Grok 4.6 vs GLM 5.2: which scores higher on benchmarks?
SpaceXAI: Grok 4.6 scores 78.0 and GLM 5.2 scores 73.2 overall on LiveBench, the mean of its seven categories. That is a 4.9-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, SpaceXAI: Grok 4.6 or GLM 5.2?
They are close. SpaceXAI: Grok 4.6 costs $0.1181 per point of overall capability and GLM 5.2 costs $0.1260, a difference small enough that workload shape will matter more than the rate.
Does SpaceXAI: Grok 4.6 or GLM 5.2 have a bigger context window?
GLM 5.2 has the larger context window: 500K for SpaceXAI: Grok 4.6 against 1.0M for GLM 5.2. 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 SpaceXAI: Grok 4.6 and GLM 5.2 support prompt caching?
Both publish a cached-input rate: $0.500 per million for SpaceXAI: Grok 4.6 and $0.193 for GLM 5.2, against full input rates of $2.00 and $0.966. On a workload with a long stable prefix — a system prompt, a tool schema, a retrieved corpus — that changes the economics more than the headline price does.
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.