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Morph V3 Fast 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.

OpenRouter + LiveBenchAll comparisonsFull leaderboard

Morph V3 Fast is the cheaper of the two; neither can be ranked on quality here.

Morph V3 Fast 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.

morph

Morph V3 Fast

Blended / 1M
$0.900
Context
82K
Released
Jul 7, 2025
Overall score
Not evaluated

z-ai

GLM 5.3

Blended / 1M
$1.29
Context
1.3M
Released
Aug 18, 2026
Overall score
76.1
reasoningtool callingprompt caching

Specs and pricing

MetricMorph V3 FastGLM 5.3
LiveBench overall

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

76.1
Cost per point

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

$0.2460
Blended price / 1M

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

$0.900win$1.29
Input price / 1M$0.800$0.840
Output price / 1M$1.20win$2.64
Cached input / 1M

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

$0.156
Context window82K1.3Mwin
Max output tokens38K131Kwin

Benchmarks by category

An overall score averages away the thing you probably care about. These are the seven LiveBench categories scored separately — Morph V3 Fast on top, GLM 5.3 below, both out of 100.

Agentic coding
60.9
Coding
79.0
Reasoning
85.8
Mathematics
87.9
Data analysis
70.2
Language
79.9
Instruction following
69.3

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.

WorkloadMorph V3 FastGLM 5.3
Support chatbot

1.2K in / 400 out × 200K requests

$288.00/mo$363.55/mo
RAG assistant

8K in / 600 out × 100K requests

$712.00/mo$556.80/mo
Coding agent

40K in / 4K out × 20K requests

$736.00/mo$500.16/mo
Document extraction

20K in / 1.5K out × 50K requests

$890.00/mo$1,004/mo
Bulk classification

500 in / 20 out × 5M requests

$2,120/mo$2,022/mo
Run these two through the cost calculator

Which should you pick?

You need to fit large documents in one call

GLM 5.3

Wider context window — 1.3M against 82K.

You are cost-constrained

Morph V3 Fast

Cheaper on blended list price at $0.900 per million tokens.

Morph V3 Fast vs GLM 5.3 FAQ

Which is better, Morph V3 Fast or GLM 5.3?

Morph V3 Fast is the cheaper of the two; neither can be ranked on quality here. Morph V3 Fast 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.

Is Morph V3 Fast cheaper than GLM 5.3?

Morph V3 Fast is cheaper. On a 3:1 input:output blend, Morph V3 Fast lists at $0.900 per million tokens and GLM 5.3 at $1.29 — Morph V3 Fast is 43% cheaper. Input and output are priced separately — Morph V3 Fast charges $0.800 in and $1.20 out, GLM 5.3 charges $0.840 and $2.64 — so the model that looks cheaper flips depending on how output-heavy your workload is.

Does Morph V3 Fast or GLM 5.3 have a bigger context window?

GLM 5.3 has the larger context window: 82K for Morph V3 Fast against 1.3M for GLM 5.3. 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 Morph V3 Fast and GLM 5.3 support prompt caching?

GLM 5.3 publishes a cached-input rate of $0.156 per million tokens against a full input rate of $0.840. The catalogue lists no separate cached rate for Morph V3 Fast, 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.
  • 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.