Tier A — Frontier

Runs in:CNMade in:China

GLM-5.1

Tier A — Frontier · 205K tokens

Tokonomix Editorial Team·Reviewed by Mes Kalkan·Published July 6, 2026·Last reviewed July 8, 2026

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 latency56 runs

Section 02

Quality scores

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

Coding

Creative

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

2026-07-122026-07-192026-07-19

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)18 / avg 64

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

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

6,441ms

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)

OK responses (30d)

Total calls (7d)

OK responses (7d)

Section 07

Tokonomix benchmark verdicts

⚖️

Endorsed by 1 judge

Independent LLM judges evaluated this model on our weekly intelligence tests

claude-sonnet-4-541/100 · 6 runs

1 correct1 partial4 wrong17% accuracy

● 2026-07-19

GLM-5.1 adds reasoning, tools, and JSON with multimodal capabilities

GLM-5.1 has expanded significantly since its debut, introducing structured output support through JSON mode, function calling tools, and a dedicated reasoning mode. These additions transform the model from a strong general-purpose system into a more versatile platform for production applications. The model now supports vision capabilities alongside its established text processing strengths, though benchmark performance data for these new modalities remains limited in the current window. Previous testing showed GLM-5.1 delivering competitive coding performance and excellent multilingual support, particularly for Chinese language tasks. The addition of reasoning mode suggests the model can now tackle more complex multi-step problems with chain-of-thought approaches. Tool calling functionality enables integration with external systems and APIs, addressing a critical gap for enterprise deployments. JSON mode provides reliable structured output generation for downstream processing. While the core model capabilities appear stable, the rapid addition of these features indicates active development. Users should expect a model that balances strong foundational performance with expanding practical utility, though comprehensive benchmarks of the new capabilities would help validate their production readiness across diverse use cases.

Quality

—

Latency p50

—

Test runs

✓ Added reasoning mode capability✓ Function calling tools introduced✓ JSON structured output support✓ Vision capabilities now available

Section 08

Full model profile

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

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

Jul 22, 2026 · 02:04 UTC · Speed benchmark

P50 latency

11007 ms

P95 latency

13364 ms

Errors

0 / 6 runs

Last reviewed by Tokonomix Team·July 8, 2026