Tier A — Frontier
Runs in:CNMade in:China
Z.ai (GLM / Zhipu)

GLM-5

Tier A — Frontier · 205K tokens

Tokonomix Editorial Team·Reviewed by Mes Kalkan··

GLM-5 is the base model of Zhipu’s GLM-5 generation on z.ai — the generation’s workhorse, priced below the GLM-5.2 flagship. It is an OpenAI-compatible reasoning chat model with tool and JSON support.

Section 01

Speed analysis

Latency measured across all benchmark runs. P50 (median) and P95 (95th percentile) give a realistic picture of response speed under normal and peak load.

P50 latency (median)P95 latency56 runs
1199575710315148721943007-0807-22ms
Section 02

Quality scores

Evaluation results from judge-model scoring across diverse task categories. Scores reflect coherence, accuracy and instruction-following.

100
Coding
98
Creative
Section 03

Pricing history

Direct provider rates per million tokens, plus a typical-conversation cost estimate.

💰
API rates — GLM-5
$1.00 per 1M input tokens
$3.20 per 1M output tokens
≈ $0.0012 per typical conversation (800 tokens)
Input vs output price (per 1M tokens)
per 1M input tokens$1.00
per 1M output tokens$3.20

Pricing over time

Input & output per 1M tokens · step-line = price changes

$1.00

input / 1M

— stable

$3.20

output / 1M

— stable

2026-07-122026-07-192026-07-19
Input
Output
Price change
⟳ synced weekly
Section 04

Tokens per second

Throughput in tokens per second, derived from measured P50 latency. Higher is better; fluctuations track provider-side load.

Throughput (tokens / s)124 / avg 87
16625

Estimated from P50 latency × 200 output tokens — the absolute number depends on this assumption; the trend is what matters.

Section 05

Capabilities

jsonnotes: GLM emits a non-standard reasoning_content field beside content; read content for the answer.toolsreasoning
Section 06

Availability

Availability

How often this model answers when we call it — measured across real API requests and live tests over the last 30 days. This is separate from quality: these numbers only tell you whether the model responds, not how good the answer is.

Last 7 days

—

Last 30 days

100.0%

n=1

Median response time

1,954ms

n=1

Based on 175 measurements over the last 30 days.

Technical details

Only live API calls and live-test requests count — internal probes and benchmark runs are excluded.

Calls with a custom API key (BYOK) are excluded: those failures are key-specific, not a sign of model downtime.

Failed calls are NOT included in quality scores — quality is measured on successful responses only. Availability and quality are independent signals.

Median response time (p50) across successful calls with a recorded duration. Outliers (very slow or very fast calls) pull the median less than the average.

Total calls (30d)

1

OK responses (30d)

1

Total calls (7d)

0

OK responses (7d)

0

Section 07

Tokonomix benchmark verdicts

⚖️
Endorsed by 1 judge
Independent LLM judges evaluated this model on our weekly intelligence tests
claude-sonnet-4-5100/100 · 6 runs
6 correct0 partial0 wrong100% accuracy
● 2026-07-19

GLM-5 adds JSON, tools, and reasoning modes in capability expansion

GLM-5 has expanded its feature set with the addition of JSON structured output, tool calling, and reasoning capabilities in this benchmark window. These are significant functional additions that broaden the model's applicability for developers building agentic systems and structured data workflows. The reasoning mode represents a notable enhancement for complex problem-solving tasks, aligning GLM-5 with emerging trends in AI model development. However, no performance benchmark data is available for this window, making it impossible to assess whether these new capabilities translate into measurable improvements in quality, speed, or accuracy compared to the previous period or competing models. The previous window highlighted strong reasoning performance, but without current metrics, users cannot determine if that strength has been maintained or improved. The lack of benchmark results also prevents evaluation of how the new JSON and tools capabilities compare to similar features in other models. For organizations considering GLM-5, the expanded capability surface is promising, but the absence of concrete performance data means deployment decisions should await more complete benchmarking information.

Quality

—

Latency p50

—

Test runs

0

✓ JSON output support added✓ Tool calling enabled✓ Reasoning mode introduced✗ No performance data available
Section 08

Full model profile

GLM-5: the base of Zhipu’s newest generation

GLM-5 is the base model of Zhipu’s GLM-5 generation on z.ai — the generation’s workhorse, priced below the GLM-5.2 flagship. It is an OpenAI-compatible reasoning chat model with tool and JSON support.

z.ai publishes GLM-5 at $1.00 per 1M input tokens and $3.20 per 1M output tokens — cheaper than the GLM-5.2 flagship while staying in the same generation.

We registered it with a large (~200K-token) context window as a provisional figure; GLM-5-generation documentation is thin, so confirm the exact window on z.ai before relying on it.

Architecture & training signals

GLM-5 is the base of Zhipu AI’s GLM-5 generation. Public technical detail is still limited as of July 2026; we treat it as a large reasoning-oriented chat model with tool-calling and structured JSON over an OpenAI-compatible endpoint. Like the rest of the GLM line, it returns a non-standard reasoning_content field alongside content in its OpenAI-compatible responses; integrations should read content for the final answer and treat reasoning_content as an optional trace.

Where it shines

  • A balanced quality-vs-price point within the newest GLM generation.
  • Long-context reasoning and analysis.
  • Cross-family diversity in a consensus panel.

Where it falls short

  • Still pricier than the GLM-4.x line and the free flash tiers.
  • Limited reproducible benchmark data; verify on your workload.
  • Non-EU hosting.

Real-world use cases

  • General reasoning where you want current-generation GLM quality without the flagship price.
  • Document analysis and summarisation.
  • Agentic tool-use pipelines.

Tokonomix benchmark snapshot

GLM-5 is newly registered on Tokonomix and not yet activated, so we have not run it through our weekly intelligence test or speed benchmark. There are no Tokonomix scores to report yet — and we will not invent any.

When it goes live, it enters the same weekly harness as every other model: identical prompts, an independent cross-family judge, and reproducible latency and cost measurements. Until then, treat the pricing and capability notes on this page as the vendor-published starting point, not as measured Tokonomix results.

EU privacy & data residency

GLM-5 is built by Zhipu AI (z.ai), a China-headquartered lab, and is served from non-EU infrastructure. This is important to state plainly: routing a prompt to this model is not an EU-data-residency or GDPR-sovereign choice, and Tokonomix will never tag it as one.

If your use case requires data to stay within the EU, pick a model whose provider is EU-hosted (for example our OVH or Azure-EU routes) rather than a GLM model. Tokonomix keeps z.ai out of every EU-only / sovereign routing set by design. Use GLM where its capability or price is the priority and cross-border processing is acceptable for that workload.

Verdict & alternatives

GLM-5 is the sensible default within the GLM-5 generation: most of the newest-generation quality at a lower price than GLM-5.2. If you need the absolute top, go GLM-5.2; if budget dominates, drop to GLM-4.6/4.5 or the free flash models.

Last automated test
Jul 22, 2026 · 02:04 UTC · Speed benchmark
P50 latency
1616 ms
P95 latency
1978 ms
Errors
0 / 6 runs
Last reviewed by Tokonomix Team·July 8, 2026