Command A vs GLM 5.1
At a Glance
| Compare |  Command ACohere |  GLM 5.1Z.ai |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $2.50Cohere ↗ · Aug 29, 2026 | $1.05Deepinfra ↗ · Sep 23, 2026 |
| Output priceFrom · USD / 1M tokens | $10.00Cohere ↗ · Aug 29, 2026 | $3.50Deepinfra ↗ · Sep 23, 2026 |
| Context windowMaximum documented tokens | 256K | 203K |
| Model facts checked | Aug 29, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Command A | GLM-5.1 |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,330.8791% of row best · rating · command-a-03-2025; 95% CI [1327.41159924, 1334.32729730]; votes 55449; rank 211 | 1,462.38100% of row best · rating · glm-5.1; 95% CI [1458.52340519, 1466.22702609]; votes 48901; rank 33 |
| Overall ResultCounted from the protocol-matched rows above | 0 benchmark winsNo overall winner | 1 benchmark winNo overall winner |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Command A | GLM-5.1 |
|---|---|---|
| Developer | Cohere | Z.ai |
| Family | Command A | Glm 5 1 |
| Model | Command A | GLM-5.1 |
| Version | Command A | GLM-5.1 |
| Lifecycle | active | active |
| Released | Unknown | Unknown |
| Knowledge cutoff | 2024-06-01 | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 256K | 203K |
| Total parameters | 111B | 753.9B |
| Active parameters | Unknown | Unknown |
| License | Unknown | mit |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Cohere (Standard) | Deepinfra (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) |
| Capabilities | agents, chat, citations, multilingual, rag, structured_outputs, tools | chat, generation, reasoning, tools |
Command A Capabilities
GLM 5.1 Capabilities
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Primary Evidence
Sources and Freshness
Questions
Command A vs GLM 5.1 FAQs
Is Command A or GLM 5.1 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Command A and GLM 5.1, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Command A or GLM 5.1?+
Command A is $2.50 and GLM 5.1 is $1.05 per million tokens, so GLM 5.1 is cheaper on this metric. Command A is $10.00 and GLM 5.1 is $3.50 per million tokens, so GLM 5.1 is cheaper on this metric.
Which has a larger context window, Command A or GLM 5.1?+
Command A has the larger sourced context window. Command A supports 256K and GLM 5.1 supports 203K.
Which performs better in benchmarks, Command A or GLM 5.1?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Command A or GLM 5.1 be self-hosted?+
GLM 5.1 is the only model in this pair currently marked as self-hostable. Command A is not marked open weight; GLM 5.1 is open weight.
Can Command A and GLM 5.1 understand images?+
Command A is not documented with image input; GLM 5.1 is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Command A or GLM 5.1?+
Neither has a larger sourced maximum output. Command A is 8K and GLM 5.1 is —.
Do Command A and GLM 5.1 support reasoning and tool use?+
Command A: tool calling. GLM 5.1: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, Command A or GLM 5.1?+
Command A has 1 sourced provider route; GLM 5.1 has 4, so GLM 5.1 has broader tracked availability.
Which offers better value, Command A or GLM 5.1?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.