Pick GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions or strong agentic coding for the price — 73.8% on swe-bench verified undercut most closed frontier models at launch. Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). On a tight budget at scale, GLM 4.7 is the value pick.
GLM 4.7 (Z.ai) and Hunyuan Hy4 Preview (Tencent) are two of the models people most often weigh against each other in 2026. GLM 4.7 is an MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Hunyuan Hy4 Preview is tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: GLM 4.7 is about 1.4× cheaper on input ($0.6/$2.2 per 1M tokens vs $0.834/$2.501 per 1M tokens) — modest, but it adds up at steady volume.
Context window: Hunyuan Hy4 Preview holds 4.9× more — 1M+ tokens (~1,500 pages) vs 200K (~304 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Hunyuan Hy4 Preview is the newer model by about 8 months (released August 28, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GLM 4.7
Hunyuan Hy4 Preview
Provider
Z.ai (China)
Tencent (China)
Released
December 22, 2025
August 28, 2026
Context window
200K (~304 pages)
1M+ tokens (~1,500 pages)
Price (in/out)
$0.6/$2.2 per 1M tokens
$0.834/$2.501 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text
SWE-Bench Verified
73.8%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions: GLM 4.7 — An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and it runs cheaper at $0.6/$2.2 per 1M tokens.
Strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch: GLM 4.7 — At $0.6/$2.2 per 1M tokens it undercuts Hunyuan Hy4 Preview ($0.834/$2.501 per 1M tokens), and that gap compounds at volume.
An unusually generous 128K maximum output, which suits bulk refactors and long generation: GLM 4.7 — GLM 4.7 lists an unusually generous 128K maximum output, which suits bulk refactors and long generation among its strengths; Hunyuan Hy4 Preview does not.
GPQA Diamond (92.3): Hunyuan Hy4 Preview — Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and it carries the larger 1M+ tokens context.
Terminal-Bench (85.4): Hunyuan Hy4 Preview — GLM 4.7 is comparatively weak here — its Verified lead narrows sharply on harder evaluations like SWE-Bench Pro
SWE-bench Multilingual (82.9): Hunyuan Hy4 Preview — Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and it is the newer of the two.
Lowest cost at scale: GLM 4.7 — At $0.6/$2.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Hunyuan Hy4 Preview — Its 1M+ tokens window is about 4.9× larger than GLM 4.7's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GLM 4.7 — At $0.6/$2.2 per 1M tokens it undercuts Hunyuan Hy4 Preview, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Hunyuan Hy4 Preview — Larger 1M+ tokens window fits more in one prompt.
Anyone whose priority is genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions: GLM 4.7 — It is specifically built for that.
Anyone whose priority is gpqa diamond (92.3): Hunyuan Hy4 Preview — That is its strongest area.
GLM 4.7: where it fits
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Released December 22, 2025 by Z.ai, it is built for genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions, strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch, an unusually generous 128K maximum output, which suits bulk refactors and long generation, and cheap long-running agent loops thanks to aggressive prompt caching.
Its trade-offs are real: two generations behind — GLM 5, 5.1 and 5.2 have all shipped since, and new builds should default to those, its Verified lead narrows sharply on harder evaluations like SWE-Bench Pro, and text-only with no vision, and self-hosting a 358B model is a serious hardware commitment. At $0.6 in / $2.2 out per million tokens, it sits in the budget price band.
Hunyuan Hy4 Preview: where it fits
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. Released August 28, 2026 by Tencent, it is built for gPQA Diamond (92.3), terminal-Bench (85.4), sWE-bench Multilingual (82.9), and large jump in long-horizon coding vs prior Hunyuan model (DeepSWE 28.0 to 64.3).
Its trade-offs: text-only, no native vision support, labeled a 'preview', not yet Tencent's finalized GA flagship, and sWE-Marathon score still low in absolute terms (31.9) despite a large relative jump. At $0.834 in / $2.501 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
GLM 4.7 and Hunyuan Hy4 Preview overlap enough that the right pick depends on your specific job. GLM 4.7 costs less per token; Hunyuan Hy4 Preview holds the larger context; and each leads in its own area — GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions, Hunyuan Hy4 Preview for gpqa diamond (92.3). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is GLM 4.7 or Hunyuan Hy4 Preview better for coding?
Public SWE-Bench figures are not available for Hunyuan Hy4 Preview, so the honest test is your own repository — run an identical real bug through both. By design, GLM 4.7 leans toward genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions while Hunyuan Hy4 Preview leans toward gpqa diamond (92.3), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 4.7 or Hunyuan Hy4 Preview?
GLM 4.7 is cheaper — $0.6/$2.2 per 1M tokens vs $0.834/$2.501 per 1M tokens, roughly 1.4× apart on input.
Which has the bigger context window?
Hunyuan Hy4 Preview — 1M+ tokens vs 200K, about 4.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 4.7 and Hunyuan Hy4 Preview together?
Yes — a multi-model platform like LumiChats gives you GLM 4.7, Hunyuan Hy4 Preview 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 4.7 or Hunyuan Hy4 Preview?
Hunyuan Hy4 Preview — released August 28, 2026, about 8 months after GLM 4.7.
GLM 4.7 vs Hunyuan Hy4 Preview
Z.ai · China | Tencent · China · Updated June 2026
Quick verdict
Pick GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions or strong agentic coding for the price — 73.8% on swe-bench verified undercut most closed frontier models at launch. Pick Hunyuan Hy4 Preview for gpqa diamond (92.3) or terminal-bench (85.4). On a tight budget at scale, GLM 4.7 is the value pick.
GLM 4.7 (Z.ai) and Hunyuan Hy4 Preview (Tencent) are two of the models people most often weigh against each other in 2026. GLM 4.7 is an MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Hunyuan Hy4 Preview is tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GLM 4.7 is about 1.4× cheaper on input ($0.6/$2.2 per 1M tokens vs $0.834/$2.501 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: Hunyuan Hy4 Preview holds 4.9× more — 1M+ tokens (~1,500 pages) vs 200K (~304 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Hunyuan Hy4 Preview is the newer model by about 8 months (released August 28, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GLM 4.7
Hunyuan Hy4 Preview
Provider
Z.ai (China)
Tencent (China)
Released
December 22, 2025
August 28, 2026
Context window
200K (~304 pages)
1M+ tokens (~1,500 pages)
Price (in/out)
$0.6/$2.2 per 1M tokens
$0.834/$2.501 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text
SWE-Bench Verified
73.8%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions
GLM 4.7
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and it runs cheaper at $0.6/$2.2 per 1M tokens.
Strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch
GLM 4.7
At $0.6/$2.2 per 1M tokens it undercuts Hunyuan Hy4 Preview ($0.834/$2.501 per 1M tokens), and that gap compounds at volume.
An unusually generous 128K maximum output, which suits bulk refactors and long generation
GLM 4.7
GLM 4.7 lists an unusually generous 128K maximum output, which suits bulk refactors and long generation among its strengths; Hunyuan Hy4 Preview does not.
GPQA Diamond (92.3)
Hunyuan Hy4 Preview
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and it carries the larger 1M+ tokens context.
Terminal-Bench (85.4)
Hunyuan Hy4 Preview
GLM 4.7 is comparatively weak here — its Verified lead narrows sharply on harder evaluations like SWE-Bench Pro
SWE-bench Multilingual (82.9)
Hunyuan Hy4 Preview
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline — and it is the newer of the two.
Lowest cost at scale
GLM 4.7
At $0.6/$2.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Hunyuan Hy4 Preview
Its 1M+ tokens window is about 4.9× larger than GLM 4.7's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GLM 4.7
At $0.6/$2.2 per 1M tokens it undercuts Hunyuan Hy4 Preview, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Hunyuan Hy4 Preview
Larger 1M+ tokens window fits more in one prompt.
Anyone whose priority is genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions
→ GLM 4.7
It is specifically built for that.
Anyone whose priority is gpqa diamond (92.3)
→ Hunyuan Hy4 Preview
That is its strongest area.
GLM 4.7: where it fits
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Released December 22, 2025 by Z.ai, it is built for genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions, strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch, an unusually generous 128K maximum output, which suits bulk refactors and long generation, and cheap long-running agent loops thanks to aggressive prompt caching.
Its trade-offs are real: two generations behind — GLM 5, 5.1 and 5.2 have all shipped since, and new builds should default to those, its Verified lead narrows sharply on harder evaluations like SWE-Bench Pro, and text-only with no vision, and self-hosting a 358B model is a serious hardware commitment. At $0.6 in / $2.2 out per million tokens, it sits in the budget price band.
Hunyuan Hy4 Preview: where it fits
Tencent's open-sourced (Apache 2.0) next-generation Hunyuan flagship preview, released August 28, 2026 as a 770B-parameter (49B active) MoE model that helped optimize its own training pipeline. Released August 28, 2026 by Tencent, it is built for gPQA Diamond (92.3), terminal-Bench (85.4), sWE-bench Multilingual (82.9), and large jump in long-horizon coding vs prior Hunyuan model (DeepSWE 28.0 to 64.3).
Its trade-offs: text-only, no native vision support, labeled a 'preview', not yet Tencent's finalized GA flagship, and sWE-Marathon score still low in absolute terms (31.9) despite a large relative jump. At $0.834 in / $2.501 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
GLM 4.7 and Hunyuan Hy4 Preview overlap enough that the right pick depends on your specific job. GLM 4.7 costs less per token; Hunyuan Hy4 Preview holds the larger context; and each leads in its own area — GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions, Hunyuan Hy4 Preview for gpqa diamond (92.3). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both GLM 4.7 and Hunyuan Hy4 Preview 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.
Is GLM 4.7 or Hunyuan Hy4 Preview better for coding?
Public SWE-Bench figures are not available for Hunyuan Hy4 Preview, so the honest test is your own repository — run an identical real bug through both. By design, GLM 4.7 leans toward genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions while Hunyuan Hy4 Preview leans toward gpqa diamond (92.3), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 4.7 or Hunyuan Hy4 Preview?
GLM 4.7 is cheaper — $0.6/$2.2 per 1M tokens vs $0.834/$2.501 per 1M tokens, roughly 1.4× apart on input.
Which has the bigger context window?
Hunyuan Hy4 Preview — 1M+ tokens vs 200K, about 4.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 4.7 and Hunyuan Hy4 Preview together?
Yes — a multi-model platform like LumiChats gives you GLM 4.7, Hunyuan Hy4 Preview 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 4.7 or Hunyuan Hy4 Preview?
Hunyuan Hy4 Preview — released August 28, 2026, about 8 months after GLM 4.7.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.