Pick GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). Pick Grok 4.3 for video understanding from native video input or generating pdf, pptx, and xlsx files directly. Choose GLM 5.1 if you need self-hosting or data privacy; Grok 4.3 if you want a managed API.
GLM 5.1 (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 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. 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
Price: nearly identical — $1.4/$4.4 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 23 days (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.
Specifications
Spec
GLM 5.1
Grok 4.3
Provider
Z.ai (China)
xAI (US)
Released
April 7, 2026
April 30, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1.4/$4.4 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
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-horizon autonomous agentic engineering (up to 8-hour runs): GLM 5.1 — A core design strength of GLM 5.1.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch): GLM 5.1 — A core design strength of GLM 5.1.
Sustained tool use across thousands of calls: GLM 5.1 — A core design strength of GLM 5.1.
Video understanding from native video input: Grok 4.3 — A core design strength of Grok 4.3.
Generating PDF, PPTX, and XLSX files directly: Grok 4.3 — A core design strength of Grok 4.3.
Real-time questions using live X data: Grok 4.3 — A core design strength of Grok 4.3.
Lowest cost at scale: Grok 4.3 — At $1.25/$2.5 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, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Grok 4.3 — At $1.25/$2.5 per 1M tokens it undercuts GLM 5.1, 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 5.1 — Open weights let you run it on your own hardware; Grok 4.3 is API-only.
Anyone whose priority is long-horizon autonomous agentic engineering (up to 8-hour runs): GLM 5.1 — 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 5.1 — Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GLM 5.1: where it fits
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.
Its trade-offs are real: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. At $1.4 in / $4.4 out per million tokens, it sits in the mid 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 5.1 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.
Frequently asked questions
Is GLM 5.1 or Grok 4.3 better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs) 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 5.1 or Grok 4.3?
GLM 5.1 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 5.1 and Grok 4.3 together?
Yes — a multi-model platform like LumiChats gives you GLM 5.1, 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 5.1 or Grok 4.3?
Grok 4.3 — released April 30, 2026, about 23 days after GLM 5.1.
GLM 5.1 vs Grok 4.3
Z.ai · China | xAI · US · Updated June 2026
Quick verdict
Pick GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). Pick Grok 4.3 for video understanding from native video input or generating pdf, pptx, and xlsx files directly. Choose GLM 5.1 if you need self-hosting or data privacy; Grok 4.3 if you want a managed API.
GLM 5.1 (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 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. 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 — $1.4/$4.4 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 23 days (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 5.1
Grok 4.3
Provider
Z.ai (China)
xAI (US)
Released
April 7, 2026
April 30, 2026
Context window
200K (~300 pages)
1M (~1,500 pages)
Price (in/out)
$1.4/$4.4 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
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-horizon autonomous agentic engineering (up to 8-hour runs)
GLM 5.1
A core design strength of GLM 5.1.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch)
GLM 5.1
A core design strength of GLM 5.1.
Sustained tool use across thousands of calls
GLM 5.1
A core design strength of GLM 5.1.
Video understanding from native video input
Grok 4.3
A core design strength of Grok 4.3.
Generating PDF, PPTX, and XLSX files directly
Grok 4.3
A core design strength of Grok 4.3.
Real-time questions using live X data
Grok 4.3
A core design strength of Grok 4.3.
Lowest cost at scale
Grok 4.3
At $1.25/$2.5 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, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Grok 4.3
At $1.25/$2.5 per 1M tokens it undercuts GLM 5.1, 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 5.1
Open weights let you run it on your own hardware; Grok 4.3 is API-only.
Anyone whose priority is long-horizon autonomous agentic engineering (up to 8-hour runs)
→ GLM 5.1
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 5.1
Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
GLM 5.1: where it fits
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.
Its trade-offs are real: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. At $1.4 in / $4.4 out per million tokens, it sits in the mid 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 5.1 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 5.1 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.
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs) 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 5.1 or Grok 4.3?
GLM 5.1 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 5.1 and Grok 4.3 together?
Yes — a multi-model platform like LumiChats gives you GLM 5.1, 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 5.1 or Grok 4.3?
Grok 4.3 — released April 30, 2026, about 23 days after GLM 5.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.