Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. Pick Qwen 3.8-Max for near-frontier quality at value pricing — artificial analysis intelligence index 58 or large 1m-token context with multimodal input (text, image, video). On a tight budget at scale, Qwen 3.8-Max is the value pick.
Command A (Cohere) and Qwen 3.8-Max (Alibaba) 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. Qwen 3.8-Max is alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: nearly identical — $2.5/$10 per 1M tokens vs $2/$6 per 1M tokens. Cost will not be the deciding factor here.
Context window: Qwen 3.8-Max holds 4.1× more — 1M (~1,573 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Qwen 3.8-Max is the newer model by about 17 months (released August 3, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Command A
Qwen 3.8-Max
Provider
Cohere (Global)
Alibaba (China)
Released
March 2025
August 3, 2026
Context window
256K (~384 pages)
1M (~1,573 pages)
Price (in/out)
$2.5/$10 per 1M tokens
$2/$6 per 1M tokens
Open weight?
No — API only
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
Enterprise RAG and retrieval: Command A — Command A lists enterprise RAG and retrieval among its strengths; Qwen 3.8-Max does not.
Strong long-context retrieval accuracy: Command A — Command A lists strong long-context retrieval accuracy among its strengths; Qwen 3.8-Max does not.
Multilingual: Command A — Command A lists multilingual among its strengths; Qwen 3.8-Max does not.
Near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58: Qwen 3.8-Max — At $2/$6 per 1M tokens it undercuts Command A ($2.5/$10 per 1M tokens), and that gap compounds at volume.
Large 1M-token context with multimodal input (text, image, video): Qwen 3.8-Max — Its 1M window holds about 4.1× more than Command A's 256K in a single prompt.
Mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token: Qwen 3.8-Max — Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped — and it runs cheaper at $2/$6 per 1M tokens.
Lowest cost at scale: Qwen 3.8-Max — At $2/$6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Qwen 3.8-Max — Its 1M window is about 4.1× larger than Command A's 256K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Qwen 3.8-Max — At $2/$6 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: Qwen 3.8-Max — Larger 1M window fits more in one prompt.
Anyone whose priority is enterprise rag and retrieval: Command A — It is specifically built for that.
Anyone whose priority is near-frontier quality at value pricing — artificial analysis intelligence index 58: Qwen 3.8-Max — 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.
Qwen 3.8-Max: where it fits
Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. Released August 3, 2026 by Alibaba, it is built for near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58, large 1M-token context with multimodal input (text, image, video), mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token, and $2/$6 per million tokens — far below US flagships like Claude Opus 5 and GPT-5.6 Sol.
Its trade-offs: open weights were announced for release but had not shipped as of mid-August 2026 — a closed API for now, active-parameter count is not officially disclosed by Alibaba, flashier coding/agentic benchmarks (e.g. Terminal-Bench 86.6) are Alibaba's own, not independently reproduced, and trails the very top models (Opus 5, Fable 5, GPT-5.6 Sol) on independent tests. At $2 in / $6 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Command A and Qwen 3.8-Max overlap enough that the right pick depends on your specific job. Qwen 3.8-Max costs less per token; Qwen 3.8-Max holds the larger context; and each leads in its own area — Command A for enterprise rag and retrieval, Qwen 3.8-Max for near-frontier quality at value pricing — artificial analysis intelligence index 58. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Command A or Qwen 3.8-Max 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, Command A leans toward enterprise rag and retrieval while Qwen 3.8-Max leans toward near-frontier quality at value pricing — artificial analysis intelligence index 58, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or Qwen 3.8-Max?
Qwen 3.8-Max is cheaper — $2.5/$10 per 1M tokens vs $2/$6 per 1M tokens, roughly 1.3× apart on input.
Which has the bigger context window?
Qwen 3.8-Max — 1M vs 256K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A and Qwen 3.8-Max together?
Yes — a multi-model platform like LumiChats gives you Command A, Qwen 3.8-Max 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 Qwen 3.8-Max?
Qwen 3.8-Max — released August 3, 2026, about 17 months after Command A.
Command A vs Qwen 3.8-Max
Cohere · Global | Alibaba · China · Updated June 2026
Quick verdict
Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. Pick Qwen 3.8-Max for near-frontier quality at value pricing — artificial analysis intelligence index 58 or large 1m-token context with multimodal input (text, image, video). On a tight budget at scale, Qwen 3.8-Max is the value pick.
Command A (Cohere) and Qwen 3.8-Max (Alibaba) 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. Qwen 3.8-Max is alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: nearly identical — $2.5/$10 per 1M tokens vs $2/$6 per 1M tokens. Cost will not be the deciding factor here.
▸Context window: Qwen 3.8-Max holds 4.1× more — 1M (~1,573 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Qwen 3.8-Max is the newer model by about 17 months (released August 3, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Command A
Qwen 3.8-Max
Provider
Cohere (Global)
Alibaba (China)
Released
March 2025
August 3, 2026
Context window
256K (~384 pages)
1M (~1,573 pages)
Price (in/out)
$2.5/$10 per 1M tokens
$2/$6 per 1M tokens
Open weight?
No — API only
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
Enterprise RAG and retrieval
Command A
Command A lists enterprise RAG and retrieval among its strengths; Qwen 3.8-Max does not.
Strong long-context retrieval accuracy
Command A
Command A lists strong long-context retrieval accuracy among its strengths; Qwen 3.8-Max does not.
Multilingual
Command A
Command A lists multilingual among its strengths; Qwen 3.8-Max does not.
Near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58
Qwen 3.8-Max
At $2/$6 per 1M tokens it undercuts Command A ($2.5/$10 per 1M tokens), and that gap compounds at volume.
Large 1M-token context with multimodal input (text, image, video)
Qwen 3.8-Max
Its 1M window holds about 4.1× more than Command A's 256K in a single prompt.
Mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token
Qwen 3.8-Max
Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped — and it runs cheaper at $2/$6 per 1M tokens.
Lowest cost at scale
Qwen 3.8-Max
At $2/$6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Qwen 3.8-Max
Its 1M window is about 4.1× larger than Command A's 256K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen 3.8-Max
At $2/$6 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
→ Qwen 3.8-Max
Larger 1M window fits more in one prompt.
Anyone whose priority is enterprise rag and retrieval
→ Command A
It is specifically built for that.
Anyone whose priority is near-frontier quality at value pricing — artificial analysis intelligence index 58
→ Qwen 3.8-Max
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.
Qwen 3.8-Max: where it fits
Alibaba's flagship mixture-of-experts model — near-frontier on independent tests (AA Index 58) at a fraction of US-flagship pricing, with open weights promised but not yet shipped. Released August 3, 2026 by Alibaba, it is built for near-frontier quality at value pricing — Artificial Analysis Intelligence Index 58, large 1M-token context with multimodal input (text, image, video), mixture-of-experts design: ~2.4T total parameters (Alibaba-reported), a fraction active per token, and $2/$6 per million tokens — far below US flagships like Claude Opus 5 and GPT-5.6 Sol.
Its trade-offs: open weights were announced for release but had not shipped as of mid-August 2026 — a closed API for now, active-parameter count is not officially disclosed by Alibaba, flashier coding/agentic benchmarks (e.g. Terminal-Bench 86.6) are Alibaba's own, not independently reproduced, and trails the very top models (Opus 5, Fable 5, GPT-5.6 Sol) on independent tests. At $2 in / $6 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Command A and Qwen 3.8-Max overlap enough that the right pick depends on your specific job. Qwen 3.8-Max costs less per token; Qwen 3.8-Max holds the larger context; and each leads in its own area — Command A for enterprise rag and retrieval, Qwen 3.8-Max for near-frontier quality at value pricing — artificial analysis intelligence index 58. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Command A and Qwen 3.8-Max 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, Command A leans toward enterprise rag and retrieval while Qwen 3.8-Max leans toward near-frontier quality at value pricing — artificial analysis intelligence index 58, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or Qwen 3.8-Max?
Qwen 3.8-Max is cheaper — $2.5/$10 per 1M tokens vs $2/$6 per 1M tokens, roughly 1.3× apart on input.
Which has the bigger context window?
Qwen 3.8-Max — 1M vs 256K, about 4.1× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A and Qwen 3.8-Max together?
Yes — a multi-model platform like LumiChats gives you Command A, Qwen 3.8-Max 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 Qwen 3.8-Max?
Qwen 3.8-Max — released August 3, 2026, about 17 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.