GLM-5.2 vs Claude Opus 4.8: Full Comparison<br>Quick verification<br>Confirm you're human to keep going.

Search models, orgs…⌘KFeedback<br>Toggle theme

The Verdict<br>GLM-5.2 is the first open-weights model to make Claude Opus 4.8 look expensive without making it look slow. Opus still holds the benchmark crown. GLM-5.2 gets close enough, on open weights, that the price gap becomes the story.<br>On June 16, 2026, Z.ai released GLM-5.2, a 753B-parameter MoE model built for long-horizon coding agents, under an MIT license. Three weeks earlier Anthropic shipped Claude Opus 4.8, its most capable general-access model. This is the comparison that matters for anyone deciding where to point an agent: the strongest open model against the strongest closed one.<br>Head to head<br>Jun 2026

A fraction of the price,<br>a few points behind.<br>Output price<br>$4.4vs$25<br>per 1M tokens

FrontierSWE gap<br>74.4vs75.1<br>dominance, within 1%

Weights<br>MIT openvsClosed<br>self-host vs API only

GLM-5.2Claude Opus 4.8<br>The short version: Opus 4.8 wins most benchmarks, with its largest margins on multi-hour software engineering and tool-use tasks. GLM-5.2 wins a handful (mostly olympiad math and one terminal-agent harness), stays within a point on a few agentic evals, and undercuts Opus on price by 3.6x to 5.7x. Here are the seven differences that decide which one you should run.

At a Glance<br>SpecGLM-5.2Claude Opus 4.8DeveloperZ.ai (Zhipu AI)AnthropicReleasedJun 16, 2026May 28, 2026LicenseMIT (open weights)ProprietaryParameters753B MoEUndisclosedContext1M tokens1M tokensMax output131K tokens128K tokensModalityText onlyText + visionEffort levelsHigh, MaxHigh, extra, maxInput price$1.40 / 1M$5.00 / 1MOutput price$4.40 / 1M$25.00 / 1MAvailabilityZ.ai, Novita, Friendli, self-hostAnthropic API, Bedrock, Vertex, Foundry

Every Benchmark, Side by Side<br>Z.ai published GLM-5.2 against Opus 4.8 on 19 reasoning, coding, and agentic benchmarks. Sorted by margin, the pattern is clean: GLM-5.2 takes the top of the chart on math and one terminal harness, then Opus 4.8 pulls ahead and the gap widens as tasks get longer and more agentic.<br>19 benchmarks<br>higher is better

GLM-5.2 wins 3,<br>Opus 4.8 takes the rest.<br>GLM-5.2Opus 4.8<br>IMOAnswerBench

+7.5<br>Terminal-Bench 2.1 (best harness)

+3.8<br>AIME 2026

+3.5<br>FrontierSWE (dominance)

−0.7<br>MCP-Atlas

−1.0<br>HMMT Nov. 2025

−2.1<br>GPQA Diamond

−2.4<br>PostTrainBench

−2.9<br>HLE (w/ tools)

−3.2<br>Terminal-Bench 2.1 (Terminus-2)

−4.0<br>CritPt

−4.2<br>HMMT Feb. 2026

−4.2<br>SWE-bench Pro

−7.1<br>ProgramBench

−8.2<br>HLE

−9.3<br>Tool-Decathlon

−11.7<br>DeepSWE

−11.8<br>SWE-Marathon

−13.0<br>NL2Repo

−20.8

Source: Z.ai GLM-5.2 technical report, June 2026. Scores are self-reported by Z.ai under matched harnesses. Delta = GLM-5.2 minus Opus 4.8.GLM-5.2 is the highest-scoring open-weights model on every one of these benchmarks. The comparison here is against the closed frontier, which is the harder test. Read the chart as “how much capability are you giving up to go open and cheap,” and the answer is: not much on reasoning, a real amount on multi-hour engineering.

1. Price: Up to 5.7x Cheaper<br>This is the headline difference. GLM-5.2 is $1.40 in / $4.40 out per million tokens. Opus 4.8 is $5 in / $25 out , and its fast mode doubles that to $10 / $50.<br>Price per million tokens<br>Input3.6x cheaper<br>GLM-5.2$1.40

Opus 4.8$5.00

Output5.7x cheaper<br>GLM-5.2$4.40

Opus 4.8$25.00

Standard API rates, June 2026. Opus 4.8 fast mode runs $10/$50. GLM-5.2 is identical on Z.ai, Novita, and Friendli serverless endpoints.For an agent that reads large repositories and writes long diffs, output tokens dominate the bill, so the 5.7x output gap is the one to feel. A workload that costs $1,000/day on Opus 4.8 output lands near $176/day on GLM-5.2. GLM-5.2 holds the same rate across Z.ai, Novita, and Friendli serverless endpoints, so the price is a property of the model, not a single vendor’s promo.

2. Open Weights vs Closed API<br>GLM-5.2 is MIT licensed with open weights on HuggingFace, runnable on vLLM, SGLang, xLLM, KTransformers, and Transformers. No regional restrictions, no API gate. You can fine-tune it, quantize it, run it air-gapped, and pin a version forever.<br>Claude Opus 4.8 is proprietary. You reach it through Anthropic’s API, Amazon Bedrock, Google Vertex AI, or Microsoft Foundry, and you accept its rate limits, deprecation schedule, and content policies. For regulated data that cannot leave your network, or for products that need a frozen model behind them, this difference outweighs every benchmark in the table.<br>One caveat in GLM-5.2’s favor on capability but against it on scope: GLM-5.2 is text only , while Opus 4.8 handles vision. If your agent reads screenshots, PDFs, or UI state from images, that is an Opus-only job today.

3. Context: Both Hit 1M<br>Context window is a tie. Both models accept a 1 million token context , and both cap output near 130K. GLM-5.2’s actual claim is not the number but the quality: it was trained specifically to hold coding-agent trajectories together across that...