
TL;DR
GLM-5.3 launched on August 14, 2026 with open weights promised in about two weeks - so the access picture is narrower than GLM-5.2's, but the free and cheap routes are already live. Here is every way to run Z.ai's newest coding model today: OpenCode Go referral credits, the GLM Coding Plan (5.3 included at no extra cost), and what to expect once the weights and third-party hosts land.
Direct answer
GLM-5.3 launched on August 14, 2026 with open weights promised in about two weeks - so the access picture is narrower than GLM-5.2's, but the free and cheap routes are already live. Here is every way to run Z.ai's newest coding model today: OpenCode Go referral credits, the GLM Coding Plan (5.3 included at no extra cost), and what to expect once the weights and third-party hosts land.
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Start here: OpenCode Go already serves GLM-5.3 with the full 1M context at the same price as GLM-5.2, and referral code M6HEHM4JM5 gives you $5 in credits plus $5 off the first month. It is the lowest-friction way to try GLM-5.3 through an agent-first interface before committing to a full plan.
| Source | What it covers |
|---|---|
| Z.ai: GLM-5.3 research blog | Official release, benchmarks, reasoning levels |
| Z.ai subscribe + model API pages | GLM Coding Plan tiers and per-token API pricing |
| OpenCode Go referral link | GLM-5.3 live day one; $5 credits plus $5 first-month promo with referral code M6HEHM4JM5 |
| OpenCode: GLM-5.3 in Go announcement | Confirms 1M context and same pricing as 5.2 |
| Z.ai devpack overview | Coding Plan quotas, credit multipliers, off-peak rates |
GLM-5.3 launched on August 14, 2026, and the access story is different from every prior GLM release in one important way: the weights are not open yet. Z.ai says the checkpoint ships in roughly two weeks, after a safety evaluation. That means the usual open-weights land rush - a dozen hosts undercutting each other within days - has not started. Today there are exactly two ways to run it: through Z.ai directly, or through OpenCode Go. Both are cheap, and one is effectively free to start.
This post maps what is live now, what it costs, and what to expect when the weights drop. Prices were verified on August 14, 2026. Pricing pages are the only source of truth and they move, so treat the numbers as a snapshot, not a contract.
Last verified: August 14, 2026.
GLM-5.3 is Z.ai's newest coding model, built on the same base as GLM-5.2 with every capability gain coming from scaled-up post-training. It keeps the 1M-token context window and adds three selectable reasoning levels (low, high, max - Z.ai recommends max for coding, and it is the default). On Z.ai's launch benchmarks it improves on GLM-5.2 across the board: 66.9 on DeepSWE v1.1, 42.5 on SWE-Marathon v1.1, and 31.4% on Z.ai's Code Bench at high effort, edging out Claude Opus 4.8's 29.5% on that last one while still trailing Claude Fable 5. Those are vendor-run numbers, not independent reproductions. Open weights are promised about two weeks after launch; until then there is no license to inspect and no self-hosting.
The GLM Coding Plan exposes an Anthropic-compatible endpoint, so pointing Claude Code at GLM-5.3 is an environment-variable swap, not a code change. Add these to your shell config (.bashrc, .zshrc, or equivalent):
export ANTHROPIC_BASE_URL="https://open.z.ai/api/paas/v4/"
export ANTHROPIC_API_KEY="your-glm-coding-plan-key"
export ANTHROPIC_DEFAULT_SONNET_MODEL="glm-5.3[1m]"
export ANTHROPIC_DEFAULT_OPUS_MODEL="glm-5.3[1m]"
export CLAUDE_CODE_AUTO_COMPACT_WINDOW=1000000
The [1m] suffix enables the 1M-context variant; without it you get the standard window. Alternatively, set the same values under env in ~/.claude/settings.json. Because the endpoint is Anthropic-compatible, existing MCP servers, skills, and hooks keep working without modification.
In OpenCode, log in to your Z.AI Coding Plan (or OpenCode Go) account and run /models to select glm-5.3 - no config edits needed.
Three paths will run GLM-5.3 with little or no upfront cost today. None is unlimited, so read the terms before you wire a production agent to them.
M6HEHM4JM5 and you get $5 in credits plus $5 off the first month. Because GLM inference is cheap, that promo stretches to a real amount of agentic coding compared with paying frontier-model rates for the same workload. If you want to try 5.3 today without touching a Z.ai account, this is the route.glm-5.3[1m] and you are done - the marginal cost of the upgrade is zero.Two free routes from the GLM-5.2 era are not here yet: there is no Hugging Face Inference Providers window and no third-party host bundling, because both depend on the open weights that have not shipped. Expect that section of the map to fill in fast once the checkpoint lands. If your goal is genuinely free and local today, GLM-5.2's weights are still on Hugging Face under MIT, and our best local models hub covers laptop-class options.
From the archive
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The competitive multi-host pricing table that makes open-weights models cheap does not exist for GLM-5.3 yet. Until the weights ship, every paid route resolves to Z.ai's infrastructure. Here is the live picture.
| Provider | Input ($/1M) | Output ($/1M) | Cached input | Context | Notes |
|---|---|---|---|---|---|
| OpenCode Go | 1.40 | 4.40 | 0.26 | 1M | Live day one, referral credits apply |
| Z.ai (first-party API) | 1.40 | 4.40 | 0.26 | 1M | GLM-5.2 rates; 5.3-specific table not yet published |
A few things worth knowing before you pick a row:
glm-5.3 must set "thinking": {"type": "enabled"} with a reasoning_effort of low, high, or max. Reasoning tokens are output tokens, so max costs more per task than the sticker price suggests. low is the lever if you are cost-sensitive.z-ai/glm-5.3 on OpenRouter yet. When the weights drop, expect the same pattern as 5.2: a dozen-plus hosts within days, fp4 routes undercutting the first-party fp8 price, and a blended rate well under Z.ai's list. See the OpenRouter profile for why the router route matters once it exists.For the worked cost-per-task math on the GLM line versus closed models, the GLM-5.2 cost math post runs the numbers - the shape carries over to 5.3.
If you go first-party, Z.ai sells two things, and they suit different usage shapes.
| Tier | Monthly | Yearly (per mo) | Weekly credits |
|---|---|---|---|
| Lite | $18 | $12.60 | 10,000 (~43-87M tokens) |
| Pro | $80 | $56 | 60,000 (~263-526M tokens) |
| Max | $168 | $117.60 | 140,000 (~613-1,226M tokens) |
The plan meters usage in credits with per-token multipliers (6.9 input, 1.7 cached input, 24 output), and off-peak usage - outside Monday to Friday 14:00-18:00 UTC+8 - is charged at 50% of the standard rate, which matters if your agents run overnight US time. Note the Pro and Max monthly prices rose versus the GLM-5.2-era tiers ($72 and $160 then). The subscription wins when you code with it daily; the API wins for spiky or automated workloads. Quotas are from Z.ai's devpack docs, so check the current terms.
This is the section that normally makes a GLM release interesting, and for GLM-5.3 it is a waiting room.
M6HEHM4JM5, or the Z.ai ZCode free quota.glm-5.3[1m]; the upgrade costs nothing.GLM-5.3 is free or nearly free in two places right now: OpenCode Go referral credits (code M6HEHM4JM5 gives $5 in credits plus $5 off the first month) and Z.ai's ZCode CLI free token quota. Existing GLM Coding Plan subscribers get it at no extra cost. There is no free hosted API window yet and no self-hosting, because the open weights have not shipped.
Today, OpenCode Go or the Z.ai API at roughly $1.40 input and $4.40 output per million tokens - they are the only hosts. Once the open weights land (promised about two weeks after the August 14, 2026 launch), expect OpenRouter, DeepInfra, and others to undercut that, as they did with GLM-5.2.
Yes. The Z.ai GLM Coding Plan supports Claude Code, Cursor, Cline, and 20-plus tools; set the model id to glm-5.3[1m] for the 1M context. In OpenCode, run /models and select glm-5.3 after logging in to OpenCode Go or a Z.AI Coding Plan.
Not yet. The weights are promised roughly two weeks after the August 14, 2026 launch, after a safety review. Until then GLM-5.2 is the self-host option in the family - same base model, MIT-licensed, on Hugging Face - though it needs datacenter-class hardware either way.
Same base model, scaled-up post-training. Z.ai's launch numbers improve on GLM-5.2 across every reported benchmark, and it adds selectable reasoning levels (low, high, max). The other practical differences are the reasoning-required API and, for now, the closed weights.
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