GLM 5 vs Grok 4.3
Z.ai · China | xAI · US · Updated June 2026
Quick verdict
Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. Pick Grok 4.3 for video understanding from native video input or generating pdf, pptx, and xlsx files directly. Choose GLM 5 if you need self-hosting or data privacy; Grok 4.3 if you want a managed API.
GLM 5 (Z.ai, China) and Grok 4.3 (xAI, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Grok 4.3 is the current xAI flagship: 1M context, native video input, file generation, and live X data, ahead of the still-unreleased Grok 5. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: nearly identical — $1/$3.2 per 1M tokens vs $1.25/$2.5 per 1M tokens. Cost will not be the deciding factor here.
- ▸Context window: Grok 4.3 holds 5× more — 1M (~1,500 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Grok 4.3 is the newer model by about 3 months (released April 30, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a China-vs-US matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | GLM 5 | Grok 4.3 |
|---|---|---|
| Provider | Z.ai (China) | xAI (US) |
| Released | February 12, 2026 | April 30, 2026 |
| Context window | 200K (~300 pages) | 1M (~1,500 pages) |
| Price (in/out) | $1/$3.2 per 1M tokens | $1.25/$2.5 per 1M tokens |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, code | text, image, video, code |
| SWE-Bench Verified | 77.8% | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Agentic planning and long-horizon coding workflows
GLM 5
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding — and it runs cheaper at $1/$3.2 per 1M tokens.
Complex systems design and backend reasoning
GLM 5
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding — and its weights are open while Grok 4.3 is API-only.
Iterative self-correction on autonomous tasks
GLM 5
GLM 5 lists iterative self-correction on autonomous tasks among its strengths; Grok 4.3 does not.
Video understanding from native video input
Grok 4.3
The current xAI flagship: 1M context, native video input, file generation, and live X data, ahead of the still-unreleased Grok 5 — and it carries the larger 1M context.
Generating PDF, PPTX, and XLSX files directly
Grok 4.3
The current xAI flagship: 1M context, native video input, file generation, and live X data, ahead of the still-unreleased Grok 5 — and it is the newer of the two.
Real-time questions using live X data
Grok 4.3
Grok 4.3 lists real-time questions using live X data among its strengths; GLM 5 does not.
Lowest cost at scale
GLM 5
At $1/$3.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Grok 4.3
Its 1M window is about 5× larger than GLM 5's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GLM 5
At $1/$3.2 per 1M tokens it undercuts Grok 4.3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Grok 4.3
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 5
Open weights let you run it on your own hardware; Grok 4.3 is API-only.
Anyone whose priority is agentic planning and long-horizon coding workflows
→ GLM 5
It is specifically built for that.
Anyone whose priority is video understanding from native video input
→ Grok 4.3
That is its strongest area.
An enterprise with regional data-residency rules
→ Grok 4.3 or GLM 5
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 12, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs are real: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
Grok 4.3: where it fits
The current xAI flagship: 1M context, native video input, file generation, and live X data, ahead of the still-unreleased Grok 5. Released April 30, 2026 by xAI, it is built for video understanding from native video input, generating PDF, PPTX, and XLSX files directly, real-time questions using live X data, and long-context, multi-agent reasoning.
Its trade-offs: higher context pricing on requests above 200K tokens, and less independent benchmark coverage than OpenAI, Anthropic, or Google. At $1.25 in / $2.5 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Grok 4.3 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both GLM 5 and Grok 4.3 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is GLM 5 or Grok 4.3 better for coding?
Public SWE-Bench figures are not available for Grok 4.3, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5 leans toward agentic planning and long-horizon coding workflows while Grok 4.3 leans toward video understanding from native video input, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or Grok 4.3?
GLM 5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Grok 4.3 is API-metered at $1.25/$2.5 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Grok 4.3 — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 5 and Grok 4.3 together?
Yes — a multi-model platform like LumiChats gives you GLM 5, Grok 4.3 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, GLM 5 or Grok 4.3?
Grok 4.3 — released April 30, 2026, about 3 months after GLM 5.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.