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

GLM-5.1

Tier A — Frontier · 205K tokens

Tokonomix Editorial Team·Reviewed by Mes Kalkan··

GLM-5.1 sits within Zhipu’s GLM-5 generation, between the GLM-5 base and the GLM-5.2 flagship. It is reachable through z.ai as an OpenAI-compatible reasoning chat model. We register it honestly with the details we can verify, and flag what we cannot.

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 latency105 runs
41275651717687001022408-1609-11ms
Section 02

Quality scores

How this model compares to the rest of the field on each prompt category, from a pairwise fit over the same prompts. The raw judge score sits underneath each number.

32%
Coding
judge mean 62
13%
Creative
judge mean 67
50%
Factual
judge mean 84
43%
Reasoning
judge mean 67

Win rate per category: how often this model beats a field-average model on a prompt from that category. 50% is average, not a failing grade. It is not a percentage of correct answers.

Section 03

Pricing history

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

💰
API rates — GLM-5.1
$1.40 per 1M input tokens
$4.40 per 1M output tokens
≈ $0.0017 per typical conversation (800 tokens)
Input vs output price (per 1M tokens)
per 1M input tokens$1.40
per 1M output tokens$4.40

Pricing over time

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

$1.40

input / 1M

— stable

$4.40

output / 1M

— stable

2026-07-122026-08-092026-09-06
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)28 / avg 30
4819

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.toolsreasoningprice note: No published price on 2026-07-06
Section 06

Availability

Availability

No measurements yet

We haven't recorded enough API calls to show availability stats for this model. Data appears once the model starts receiving live traffic.

Section 07

Tokonomix benchmark verdicts

⚖️
Endorsed by 1 judge
Independent LLM judges evaluated this model on our weekly intelligence tests
claude-sonnet-4-569/100 · 28 runs
16 correct2 partial10 wrong57% accuracy
2026-09-06

GLM-5.1 shows significant quality decline, latency degrades

GLM-5.1 has experienced a substantial performance regression in this benchmark window. Overall quality dropped 24.5 points from 97.0 to 72.5, marking a concerning decline in model capabilities. The coding category, previously at a perfect 100, fell to 73, while factual and reasoning categories that scored 91 and 100 respectively are no longer represented in current results with only 2 test runs compared to 3 previously. Latency has also worsened considerably, with p50 response times increasing 37% from 16981ms to 23211ms, now exceeding 23 seconds for typical requests. This combination of degraded output quality and slower response times represents a notable step backward for the model. The limited test run data in the current window may indicate reduced stability or availability. Users should be aware that GLM-5.1 is currently underperforming relative to its previous capabilities across both quality and speed metrics. The dramatic shift suggests potential infrastructure issues, model changes, or other operational factors affecting performance that warrant attention from the development team.

Quality

72.5

Latency p50

23,211 ms

Test runs

2

Quality dropped 24.5 points Latency increased 37% Coding score fell to 73 Fewer test runs completed
Section 08

Full model profile

GLM-5.1: a GLM-5 generation model on z.ai

GLM-5.1 sits within Zhipu’s GLM-5 generation, between the GLM-5 base and the GLM-5.2 flagship. It is reachable through z.ai as an OpenAI-compatible reasoning chat model. We register it honestly with the details we can verify, and flag what we cannot.

z.ai had not published a public price for GLM-5.1 at the time we registered it (July 2026), so we store no billing figures for it. Confirm the current rate on z.ai before activating it.

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-5.1 is part of the GLM-5 generation from Zhipu AI. As with the rest of the GLM-5 series, deep public technical documentation is limited as of July 2026. We treat it as a large reasoning-oriented chat model with tool and JSON support 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

  • General reasoning and long-context tasks within the GLM-5 generation.
  • A cross-family alternative to US frontier models in a consensus panel.
  • Tool-calling and structured JSON output.

Where it falls short

  • No published price at registration — activate only after confirming the current rate.
  • Sparse independent benchmark coverage; validate on your own tasks.
  • Non-EU hosting.

Real-world use cases

  • A decorrelated second opinion in multi-model consensus.
  • Long-document analysis and summarisation.
  • Agentic tasks needing tool-calls.

Tokonomix benchmark snapshot

GLM-5.1 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-5.1 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-5.1 is a mid-point of the GLM-5 generation. Because its price was unpublished when we registered it, treat activation as a deliberate step: confirm the rate first. If you simply want the newest GLM quality, GLM-5.2 is the documented flagship; for value, GLM-4.7/4.6.

Last automated test
Sep 11, 2026 · 08:04 UTC · Speed benchmark
P50 latency
7046 ms
P95 latency
8227 ms
Errors
0 / 6 runs
Last reviewed by Tokonomix Team·July 8, 2026