// head_to_head

SpaceXAI: Grok Build 0.1 vs GLM 5.3 Flash

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.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

GLM 5.3 Flash wins outright — it scores higher and costs less.

GLM 5.3 Flash leads by 3.8 points overall while listing 11× cheaper per blended million tokens. There is no trade-off to reason about here; the only reason to pick the other is a constraint this table does not show, like an existing contract, a region, or a provider you are already on.

x-ai

SpaceXAI: Grok Build 0.1

Blended / 1M
$1.25
Context
256K
Released
May 20, 2026
Overall score
67.8
reasoningtool callingimage inputfile inputprompt caching

z-ai

GLM 5.3 Flash

Blended / 1M
$0.119
Context
1.3M
Released
Aug 26, 2026
Overall score
71.6
reasoningtool callingimage inputvideo inputprompt caching

Specs and pricing

MetricSpaceXAI: Grok Build 0.1GLM 5.3 Flash
LiveBench overall

Mean of the seven LiveBench category scores, 0–100. Higher is better.

67.871.6win
Cost per point

Measured benchmark spend divided by overall score — dollars per point of capability.

$0.0144$0.0161
Blended price / 1M

3:1 input:output mix, the usual shape of production traffic.

$1.25$0.119win
Input price / 1M$1.00$0.075win
Output price / 1M$2.00$0.250win
Cached input / 1M

Price of an input token served from the prompt cache, where the provider publishes one.

$0.200$0.015win
Context window256K1.3Mwin
Max output tokens230Kwin131K

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — SpaceXAI: Grok Build 0.1 on top, GLM 5.3 Flash below, both out of 100.

Agentic coding
45.8
56.8
Coding
65.4
79.0
Reasoning
76.4
77.6
Mathematics
78.4
81.2
Data analysis
70.8
76.4
Language
72.5
77.3
Instruction following
65.2
52.8

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.

WorkloadSpaceXAI: Grok Build 0.1GLM 5.3 Flash
Support chatbot

1.2K in / 400 out × 200K requests

$342.40/mo$33.68/mo
RAG assistant

8K in / 600 out × 100K requests

$600.00/mo$51.00/mo
Coding agent

40K in / 4K out × 20K requests

$512.00/mo$46.40/mo
Document extraction

20K in / 1.5K out × 50K requests

$1110.00/mo$90.75/mo
Bulk classification

500 in / 20 out × 5M requests

$2300.00/mo$182.50/mo
Run these two through the cost calculator

Which should you pick?

Quality matters more than the bill

GLM 5.3 Flash

Highest overall LiveBench score of the two at 71.6.

The workload is coding or agentic work

GLM 5.3 Flash

Leads on agentic coding — 56.8 against 45.8.

You need to fit large documents in one call

GLM 5.3 Flash

Wider context window — 1.3M against 256K.

SpaceXAI: Grok Build 0.1 vs GLM 5.3 Flash FAQ

Which is better, SpaceXAI: Grok Build 0.1 or GLM 5.3 Flash?

GLM 5.3 Flash wins outright — it scores higher and costs less. GLM 5.3 Flash leads by 3.8 points overall while listing 11× cheaper per blended million tokens. There is no trade-off to reason about here; the only reason to pick the other is a constraint this table does not show, like an existing contract, a region, or a provider you are already on.

Is SpaceXAI: Grok Build 0.1 cheaper than GLM 5.3 Flash?

GLM 5.3 Flash is cheaper. On a 3:1 input:output blend, SpaceXAI: Grok Build 0.1 lists at $1.25 per million tokens and GLM 5.3 Flash at $0.119 — GLM 5.3 Flash is 11× cheaper. Input and output are priced separately — SpaceXAI: Grok Build 0.1 charges $1.00 in and $2.00 out, GLM 5.3 Flash charges $0.075 and $0.250 — so the model that looks cheaper flips depending on how output-heavy your workload is.

SpaceXAI: Grok Build 0.1 vs GLM 5.3 Flash: which scores higher on benchmarks?

SpaceXAI: Grok Build 0.1 scores 67.8 and GLM 5.3 Flash scores 71.6 overall on LiveBench, the mean of its seven categories. That is a 3.8-point lead for GLM 5.3 Flash. 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 Build 0.1 or GLM 5.3 Flash?

They are close. SpaceXAI: Grok Build 0.1 costs $0.0144 per point of overall capability and GLM 5.3 Flash costs $0.0161, a difference small enough that workload shape will matter more than the rate.

Does SpaceXAI: Grok Build 0.1 or GLM 5.3 Flash have a bigger context window?

GLM 5.3 Flash has the larger context window: 256K for SpaceXAI: Grok Build 0.1 against 1.3M for GLM 5.3 Flash. 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 Build 0.1 and GLM 5.3 Flash support prompt caching?

Both publish a cached-input rate: $0.200 per million for SpaceXAI: Grok Build 0.1 and $0.015 for GLM 5.3 Flash, against full input rates of $1.00 and $0.075. 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.
  • ScoresLiveBench 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.