// head_to_head
Step 5 Preview vs GLM 5.3
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.
Step 5 Preview scores higher, GLM 5.3 costs less — it depends on your workload.
Step 5 Preview is ahead by 1.3 points overall, and GLM 5.3 lists 13% cheaper per blended million tokens. Whether 1.3 points is worth that depends on how much a wrong answer costs you. GLM 5.3 also leads on measured cost per point of capability, at $1.55 per point.
stepfun
Step 5 Preview
- Blended / 1M
- $1.43
- Context
- 1.0M
- Released
- Oct 8, 2026
- Overall score
- 62.0
z-ai
GLM 5.3
- Blended / 1M
- $1.26
- Context
- 1.0M
- Released
- Aug 18, 2026
- Overall score
- 60.7
Specs and pricing
| Metric | Step 5 Preview | GLM 5.3 |
|---|---|---|
| LiveBench overall Mean of the seven LiveBench category scores, 0–100. Higher is better. | 62.0win | 60.7 |
| Cost per point Measured benchmark spend divided by overall score — dollars per point of capability. | $4.08 | $1.55win |
| Blended price / 1M 3:1 input:output mix, the usual shape of production traffic. | $1.43 | $1.26win |
| Input price / 1M | $1.00 | $0.079win |
| Output price / 1M | $2.70win | $4.80 |
| Cached input / 1M Price of an input token served from the prompt cache, where the provider publishes one. | $0.100 | $0.078win |
| Context window | 1.0M | 1.0M |
| Max output tokens | 64K | 944Kwin |
Benchmarks by category
An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Step 5 Preview on top, GLM 5.3 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 | Step 5 Preview | GLM 5.3 |
|---|---|---|
| Support chatbot 1.2K in / 400 out × 200K requests | $391.20/mo | $402.89/mo |
| RAG assistant 8K in / 600 out × 100K requests | $602.00/mo | $350.80/mo |
| Coding agent 40K in / 4K out × 20K requests | $512.00/mo | $446.64/mo |
| Document extraction 20K in / 1.5K out × 50K requests | $1,158/mo | $438.95/mo |
| Bulk classification 500 in / 20 out × 5M requests | $2,320/mo | $677.00/mo |
Which should you pick?
You are running this at volume
GLM 5.3
Lowest measured cost per point of capability at $1.55 per point — the gap compounds with every request.
Quality matters more than the bill
Step 5 Preview
Highest overall LiveBench score of the two at 62.0.
The workload is coding or agentic work
Step 5 Preview
Leads on coding — 85.6 against 82.8.
Step 5 Preview vs GLM 5.3 FAQ
Which is better, Step 5 Preview or GLM 5.3?
Step 5 Preview scores higher, GLM 5.3 costs less — it depends on your workload. Step 5 Preview is ahead by 1.3 points overall, and GLM 5.3 lists 13% cheaper per blended million tokens. Whether 1.3 points is worth that depends on how much a wrong answer costs you. GLM 5.3 also leads on measured cost per point of capability, at $1.55 per point.
Is Step 5 Preview cheaper than GLM 5.3?
GLM 5.3 is cheaper. On a 3:1 input:output blend, Step 5 Preview lists at $1.43 per million tokens and GLM 5.3 at $1.26 — GLM 5.3 is 13% cheaper. Input and output are priced separately — Step 5 Preview charges $1.00 in and $2.70 out, GLM 5.3 charges $0.079 and $4.80 — so the model that looks cheaper flips depending on how output-heavy your workload is.
Step 5 Preview vs GLM 5.3: which scores higher on benchmarks?
Step 5 Preview scores 62.0 and GLM 5.3 scores 60.7 overall on LiveBench, the mean of its seven categories. That is a 1.3-point lead for Step 5 Preview. 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, Step 5 Preview or GLM 5.3?
GLM 5.3. 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. Step 5 Preview works out at $4.08 per point and GLM 5.3 at $1.55.
Does Step 5 Preview or GLM 5.3 have a bigger context window?
They are effectively the same — 1.0M for Step 5 Preview and 1.0M for GLM 5.3.
Do Step 5 Preview and GLM 5.3 support prompt caching?
Both publish a cached-input rate: $0.100 per million for Step 5 Preview and $0.078 for GLM 5.3, against full input rates of $1.00 and $0.079. 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 2026-09-02, 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.