Pick DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable or 1m-token context with up to 384k output tokens. 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. On a tight budget at scale, DeepSeek V4-Pro is the value pick.
DeepSeek V4-Pro (DeepSeek) and GLM 4.7 (Z.ai) are two of the models people most often weigh against each other in 2026. DeepSeek V4-Pro is deepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. 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. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: DeepSeek V4-Pro is about 1.4× cheaper on input ($0.435/$0.87 per 1M tokens vs $0.6/$2.2 per 1M tokens) — modest, but it adds up at steady volume.
Context window: DeepSeek V4-Pro holds 4.9× more — 1M (~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: DeepSeek V4-Pro is the newer model by about 4 months (released April 24, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
DeepSeek V4-Pro
GLM 4.7
Provider
DeepSeek (China)
Z.ai (China)
Released
April 24, 2026
December 22, 2025
Context window
1M (~1,500 pages)
200K (~304 pages)
Price (in/out)
$0.435/$0.87 per 1M tokens
$0.6/$2.2 per 1M tokens
Open weight?
Yes — self-hostable
Yes — self-hostable
Modalities
text, code
text, code
SWE-Bench Verified
Not published
73.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable: DeepSeek V4-Pro — DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it runs cheaper at $0.435/$0.87 per 1M tokens.
1M-token context with up to 384K output tokens: DeepSeek V4-Pro — Its 1M window holds about 4.9× more than GLM 4.7's 200K in a single prompt.
Permanent low pricing at $0.435/$0.87 per million, set May 2026: DeepSeek V4-Pro — DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it carries the larger 1M context.
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions: GLM 4.7 — GLM 4.7 lists genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions among its strengths; DeepSeek V4-Pro does not.
Strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch: GLM 4.7 — DeepSeek V4-Pro is comparatively weak here — independent SWE-Bench Verified placement is inconsistent across sources
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; DeepSeek V4-Pro does not.
Lowest cost at scale: DeepSeek V4-Pro — At $0.435/$0.87 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: DeepSeek V4-Pro — Its 1M 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: DeepSeek V4-Pro — At $0.435/$0.87 per 1M tokens it undercuts GLM 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: DeepSeek V4-Pro — Larger 1M window fits more in one prompt.
Anyone whose priority is open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable: DeepSeek V4-Pro — It is specifically built for that.
Anyone whose priority is genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions: GLM 4.7 — That is its strongest area.
DeepSeek V4-Pro: where it fits
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Released April 24, 2026 by DeepSeek, it is built for open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable, 1M-token context with up to 384K output tokens, permanent low pricing at $0.435/$0.87 per million, set May 2026, and sources place it near the top of open-weight coding, around 80 on SWE-Bench Verified.
Its trade-offs are real: independent SWE-Bench Verified placement is inconsistent across sources, pro and Pro-Max variants are quoted with different scores, text and code only — no image, audio or video, and overlaps DeepSeek V4 and V3.2 already in this comparison. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
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: 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.
The bottom line for this matchup
DeepSeek V4-Pro and GLM 4.7 overlap enough that the right pick depends on your specific job. DeepSeek V4-Pro costs less per token; DeepSeek V4-Pro holds the larger context; and each leads in its own area — DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable, GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is DeepSeek V4-Pro or GLM 4.7 better for coding?
Public SWE-Bench figures are not available for DeepSeek V4-Pro, so the honest test is your own repository — run an identical real bug through both. By design, DeepSeek V4-Pro leans toward open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable while GLM 4.7 leans toward genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4-Pro or GLM 4.7?
DeepSeek V4-Pro is cheaper — $0.435/$0.87 per 1M tokens vs $0.6/$2.2 per 1M tokens, roughly 1.4× apart on input.
Which has the bigger context window?
DeepSeek V4-Pro — 1M 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 DeepSeek V4-Pro and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Pro, GLM 4.7 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, DeepSeek V4-Pro or GLM 4.7?
DeepSeek V4-Pro — released April 24, 2026, about 4 months after GLM 4.7.
DeepSeek V4-Pro vs GLM 4.7
DeepSeek · China | Z.ai · China · Updated June 2026
Quick verdict
Pick DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable or 1m-token context with up to 384k output tokens. 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. On a tight budget at scale, DeepSeek V4-Pro is the value pick.
DeepSeek V4-Pro (DeepSeek) and GLM 4.7 (Z.ai) are two of the models people most often weigh against each other in 2026. DeepSeek V4-Pro is deepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. 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. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: DeepSeek V4-Pro is about 1.4× cheaper on input ($0.435/$0.87 per 1M tokens vs $0.6/$2.2 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: DeepSeek V4-Pro holds 4.9× more — 1M (~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: DeepSeek V4-Pro is the newer model by about 4 months (released April 24, 2026), usually meaning fresher training data and capabilities.
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it runs cheaper at $0.435/$0.87 per 1M tokens.
1M-token context with up to 384K output tokens
DeepSeek V4-Pro
Its 1M window holds about 4.9× more than GLM 4.7's 200K in a single prompt.
Permanent low pricing at $0.435/$0.87 per million, set May 2026
DeepSeek V4-Pro
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it carries the larger 1M context.
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions
GLM 4.7
GLM 4.7 lists genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions among its strengths; DeepSeek V4-Pro does not.
Strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch
GLM 4.7
DeepSeek V4-Pro is comparatively weak here — independent SWE-Bench Verified placement is inconsistent across sources
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; DeepSeek V4-Pro does not.
Lowest cost at scale
DeepSeek V4-Pro
At $0.435/$0.87 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
DeepSeek V4-Pro
Its 1M 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
→ DeepSeek V4-Pro
At $0.435/$0.87 per 1M tokens it undercuts GLM 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
Anyone whose priority is genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions
→ GLM 4.7
That is its strongest area.
DeepSeek V4-Pro: where it fits
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Released April 24, 2026 by DeepSeek, it is built for open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable, 1M-token context with up to 384K output tokens, permanent low pricing at $0.435/$0.87 per million, set May 2026, and sources place it near the top of open-weight coding, around 80 on SWE-Bench Verified.
Its trade-offs are real: independent SWE-Bench Verified placement is inconsistent across sources, pro and Pro-Max variants are quoted with different scores, text and code only — no image, audio or video, and overlaps DeepSeek V4 and V3.2 already in this comparison. At $0.435 in / $0.87 out per million tokens, it sits in the budget price band.
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: 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.
The bottom line for this matchup
DeepSeek V4-Pro and GLM 4.7 overlap enough that the right pick depends on your specific job. DeepSeek V4-Pro costs less per token; DeepSeek V4-Pro holds the larger context; and each leads in its own area — DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable, GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both DeepSeek V4-Pro and GLM 4.7 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 DeepSeek V4-Pro, so the honest test is your own repository — run an identical real bug through both. By design, DeepSeek V4-Pro leans toward open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable while GLM 4.7 leans toward genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek V4-Pro or GLM 4.7?
DeepSeek V4-Pro is cheaper — $0.435/$0.87 per 1M tokens vs $0.6/$2.2 per 1M tokens, roughly 1.4× apart on input.
Which has the bigger context window?
DeepSeek V4-Pro — 1M 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 DeepSeek V4-Pro and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Pro, GLM 4.7 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, DeepSeek V4-Pro or GLM 4.7?
DeepSeek V4-Pro — released April 24, 2026, about 4 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.