Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. 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. Choose GLM 4.7 if you need self-hosting or data privacy; Command A if you want a managed API.
Command A (Cohere) and GLM 4.7 (Z.ai) are two of the models people most often weigh against each other in 2026. Command A is cohere's enterprise-focused model built for retrieval-augmented and grounded workloads. 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, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: GLM 4.7 is about 4.2× cheaper on input ($0.6/$2.2 per 1M tokens vs $2.5/$10 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Command A holds 1.3× more — 256K (~384 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: GLM 4.7 is the newer model by about 10 months (released December 22, 2025), usually meaning fresher training data and capabilities.
Specifications
Spec
Command A
GLM 4.7
Provider
Cohere (Global)
Z.ai (China)
Released
March 2025
December 22, 2025
Context window
256K (~384 pages)
200K (~304 pages)
Price (in/out)
$2.5/$10 per 1M tokens
$0.6/$2.2 per 1M tokens
Open weight?
No — API only
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
Enterprise RAG and retrieval: Command A — Cohere's enterprise-focused model built for retrieval-augmented and grounded workloads — and it carries the larger 256K context.
Strong long-context retrieval accuracy: Command A — Its 256K window holds about 1.3× more than GLM 4.7's 200K in a single prompt.
Multilingual: Command A — Command A lists multilingual among its strengths; GLM 4.7 does not.
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions: GLM 4.7 — Open weights make this possible at all — Command A is API-only, so it cannot leave the vendor's servers.
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 Command A ($2.5/$10 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 — 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.
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: Command A — Its 256K window is about 1.3× larger than GLM 4.7's 200K, fitting roughly 384 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 Command A, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Command A — Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs: GLM 4.7 — Open weights let you run it on your own hardware; Command A is API-only.
Anyone whose priority is enterprise rag and retrieval: Command A — 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.
Command A: where it fits
Cohere's enterprise-focused model built for retrieval-augmented and grounded workloads. Released March 2025 by Cohere, it is built for enterprise RAG and retrieval, strong long-context retrieval accuracy, multilingual, and tool use.
Its trade-offs are real: less consumer presence, and narrower modality support. At $2.5 in / $10 out per million tokens, it sits in the mid 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
The defining split here is open vs. closed. GLM 4.7 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Command A 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 Command A or GLM 4.7 better for coding?
Public SWE-Bench figures are not available for Command A, so the honest test is your own repository — run an identical real bug through both. By design, Command A leans toward enterprise rag and retrieval 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, Command A or GLM 4.7?
GLM 4.7 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Command A is API-metered at $2.5/$10 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?
Command A — 256K vs 200K, about 1.3× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you Command A, 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, Command A or GLM 4.7?
GLM 4.7 — released December 22, 2025, about 10 months after Command A.
Command A vs GLM 4.7
Cohere · Global | Z.ai · China · Updated June 2026
Quick verdict
Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. 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. Choose GLM 4.7 if you need self-hosting or data privacy; Command A if you want a managed API.
Command A (Cohere) and GLM 4.7 (Z.ai) are two of the models people most often weigh against each other in 2026. Command A is cohere's enterprise-focused model built for retrieval-augmented and grounded workloads. 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, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GLM 4.7 is about 4.2× cheaper on input ($0.6/$2.2 per 1M tokens vs $2.5/$10 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Command A holds 1.3× more — 256K (~384 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: GLM 4.7 is the newer model by about 10 months (released December 22, 2025), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Command A
GLM 4.7
Provider
Cohere (Global)
Z.ai (China)
Released
March 2025
December 22, 2025
Context window
256K (~384 pages)
200K (~304 pages)
Price (in/out)
$2.5/$10 per 1M tokens
$0.6/$2.2 per 1M tokens
Open weight?
No — API only
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
Enterprise RAG and retrieval
Command A
Cohere's enterprise-focused model built for retrieval-augmented and grounded workloads — and it carries the larger 256K context.
Strong long-context retrieval accuracy
Command A
Its 256K window holds about 1.3× more than GLM 4.7's 200K in a single prompt.
Multilingual
Command A
Command A lists multilingual among its strengths; GLM 4.7 does not.
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions
GLM 4.7
Open weights make this possible at all — Command A is API-only, so it cannot leave the vendor's servers.
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 Command A ($2.5/$10 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
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.
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
Command A
Its 256K window is about 1.3× larger than GLM 4.7's 200K, fitting roughly 384 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 Command A, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Command A
Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 4.7
Open weights let you run it on your own hardware; Command A is API-only.
Anyone whose priority is enterprise rag and retrieval
→ Command A
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.
Command A: where it fits
Cohere's enterprise-focused model built for retrieval-augmented and grounded workloads. Released March 2025 by Cohere, it is built for enterprise RAG and retrieval, strong long-context retrieval accuracy, multilingual, and tool use.
Its trade-offs are real: less consumer presence, and narrower modality support. At $2.5 in / $10 out per million tokens, it sits in the mid 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
The defining split here is open vs. closed. GLM 4.7 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Command A 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 Command A 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 Command A, so the honest test is your own repository — run an identical real bug through both. By design, Command A leans toward enterprise rag and retrieval 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, Command A or GLM 4.7?
GLM 4.7 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Command A is API-metered at $2.5/$10 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?
Command A — 256K vs 200K, about 1.3× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you Command A, 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, Command A or GLM 4.7?
GLM 4.7 — released December 22, 2025, about 10 months after Command A.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.