Model comparison

GLM 5.3 vs GPT-5.6 Sol

Z.ai against OpenAI, compared on context, price, and verified benchmark results.

Catalog record checked August 14, 2026; individual provider fields may change.

Z.ai

GLM 5.3

Frontier

OpenAI

GPT-5.6 Sol

Frontier

AI model capability comparison
Specification	GLM 5.3	GPT-5.6 Sol
Provider	Z.ai	OpenAI
Tier	Frontier	Frontier
Context window	1M	Winner: 1.05M
Max output	128K	128K
Input / 1M tokens	Not verified	$5
Output / 1M tokens	Not verified	$30
Weights	Closed	Closed
Parameters	Not disclosed	Not disclosed
Reasoning levels	low, high, max	none, low, medium, high, xhigh, max
Modalities	text	text, image
Released	August 14, 2026	July 9, 2026
Artificial Analysis Intelligence Index [max] (2026-08-08)	Not verified	61

Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Pricing tiers: GLM 5.3: Direct `glm-5.3` API is documented as coming soon and is not on the Z.ai per-token table (do not assume GLM 5.2's $1.40/$4.40). Today it is on every GLM Coding Plan: points-based quota (input / cached input / output). Off-peak is 50% of standard points. Peak is Monday–Friday 14:00–18:00 UTC+8. Coding Plan requests for GLM-5.2/5.1 are routed to 5.3. · GPT-5.6 Sol: Prompts above 272K tokens bill at 2× input and 1.5× output; cache writes are 1.25× the input rate.

Frontier

GLM 5.3

Z.ai's 2026-08-14 Coding Plan flagship — same base as GLM 5.2, with the documented gains from post-training only. Direct token API and open weights are not published yet.

Best for

GLM Coding Plan agent work
Long-horizon coding in Claude Code / OpenCode / Cline
Teams already on Z.ai subscriptions

Watch out

Thinking cannot be disabled (`thinking.type: disabled` fails); `reasoning_effort` is low / high / max (default max). Open weights are promised about two weeks after launch pending safety review — not a downloadable checkpoint today. Vendor DeepSWE v1.1 66.9 used mini-swe-agent at 400K context, not the public Datacurve v1.1 board (snapshot generated 2026-08-13, before this launch).

Frontier

GPT-5.6 Sol

OpenAI's flagship tier, aimed at the hardest reasoning and agentic work.

Best for

Complex reasoning
Agentic workflows
Hard coding tasks

Watch out

25x Luna's input price — overspecified for routine generation. Sol Fast mode (where offered) is roughly ~2× price for ~2.5× speed — only enable when latency is the constraint. `gpt-5.2-chat-latest` / `gpt-5.3-chat-latest` shut down 2026-08-10 — migrate API chat traffic to Sol. ChatGPT Plus/Pro Chat got an Aug 6 Sol refresh + effort slider; Work/Codex/API July builds are unchanged.

Benchmark

DeepSWE 1.1 in context

Only GPT-5.6 Sol has a published DeepSWE 1.1 result. It is shown against the wider field, with cost per completed task alongside the score.

Local leader

Claude Opus 5 [max]

74%

Rows shown

Highest published reasoning effort per model (not best Pass@1)

Snapshot date

2026-08-13

Mirrored from deepswe.datacurve.ai

Better is toward the top-right (higher pass rate, lower cost). X-axis is reversed to match DeepSWE’s public chart. v1.1 uses average cost / tokens / steps; v1 uses published medians.

DeepSWE 1.1 leaderboard with pass rate, cost, tokens, and steps per task
#	Model	Pass@1	Cost / task	Tokens / task	Steps / task
1	Claude Opus 5 [max]	74%	$11.84	118k	99
2	GPT-5.6 Sol [max]	73%	$8.39	60k	61
3	Claude Fable 5 [max]	70%	$21.63	119k	88
4	GPT-5.6 Terra [max]	70%	$4.95	72k	76
5	Kimi K3 [max]	69%	$4.65	82k	98
6	GPT-5.6 Luna [max]	67%	$3.03	73k	102
7	GPT-5.5 [xhigh]	67%	$7.23	46k	82
8	Grok 4.6 [xhigh]	67%	$5.50	71k	87
9	Gemini 3.7 Flash [high]	65%	$2.18	107k	125
10	DeepSeek V4-Pro [max]	63%	$0.24	106k	155
11	Claude Opus 4.8 [max]	59%	$13.22	135k	120
12	Qwen3.8-Max [xhigh]	58%	$3.73	95k	111
13	Muse Spark 1.2 [xhigh]	55%	$3.70	99k	101
14	Claude Sonnet 5 [max]	54%	$26.40	214k	268
15	Grok 4.5 [high]	54%	$2.42	36k	61
16	DeepSeek V4-Flash [max]	53%	$0.10	108k	153
17	Muse Spark 1.1 [xhigh]	53%	$2.36	74k	96
18	GPT-5.4 [xhigh]	52%	$5.65	71k	70
19	Gemini 3.6 Flash [high]	47%	$4.42	96k	117
20	GLM 5.2 [max]	44%	$3.92	78k	129
21	Gemini 3.5 Flash [high]	36%	$3.45	76k	105
22	Kimi K2.7 Code	31%	$2.82	59k	149
23	Claude Sonnet 4.6 [high]	30%	$5.52	76k	134
24	Gemini 3.1 Pro [high]	12%	$2.14	28k	76

DeepSWE “Best” picks the highest published reasoning effort per model (not the highest pass rate). Small gaps may not be statistically meaningful — confirm on deepswe.datacurve.ai.

Common questions

GLM 5.3 vs GPT-5.6 Sol

Answered from the verified figures on this page rather than general guidance.

Which has the larger context window, GLM 5.3 or GPT-5.6 Sol?

GPT-5.6 Sol accepts 1.05M tokens against 1M for GLM 5.3. This only matters if you routinely send very long documents or large codebases.

Do GLM 5.3 and GPT-5.6 Sol support the same reasoning levels?

GLM 5.3 exposes low, high, max, while GPT-5.6 Sol exposes none, low, medium, high, xhigh, max.

Should I use GLM 5.3 or GPT-5.6 Sol?

Both sit in the frontier tier, so the choice usually comes down to price and context rather than capability. GLM 5.3 suits glm coding plan agent work; GPT-5.6 Sol suits complex reasoning.

Next step

Choosing between them

Tier and workload decide this more reliably than a leaderboard position does.

If both sit in the same tier, the decision usually comes down to context window and output price rather than headline capability — output tokens dominate real bills.

If one is a step up within the same provider, the useful question is whether your hardest task actually fails on the cheaper tier. Most production volume — classification, extraction, summarization — does not.

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