Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. Pick Qwen3.6 35B A3B for extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost or runs at roughly 120 tokens per second on a single 24gb consumer gpu. Choose Qwen3.6 35B A3B if you need self-hosting or data privacy; Command A if you want a managed API.
Command A (Cohere) and Qwen3.6 35B A3B (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. Qwen3.6 35B A3B is a sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Qwen3.6 35B A3B ships open weights you can self-host (hardware cost only, no per-token fee), while Command A is API-metered at $2.5/$10 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: 256K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: Qwen3.6 35B A3B is the newer model by about 14 months (released April 16, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Command A
Qwen3.6 35B A3B
Provider
Cohere (Global)
Alibaba (China)
Released
March 2025
April 16, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
$2.5/$10 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
73.4%
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; Qwen3.6 35B A3B does not.
Strong long-context retrieval accuracy: Command A — Command A lists strong long-context retrieval accuracy among its strengths; Qwen3.6 35B A3B does not.
Multilingual: Command A — Command A lists multilingual among its strengths; Qwen3.6 35B A3B does not.
Extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost: Qwen3.6 35B A3B — A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware — and its weights are open while Command A is API-only.
Runs at roughly 120 tokens per second on a single 24GB consumer GPU: Qwen3.6 35B A3B — Command A is comparatively weak here — less consumer presence
Apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN: Qwen3.6 35B A3B — A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware — and it is the newer of the two.
Lowest cost at scale: Qwen3.6 35B A3B — Its weights are open, so at volume you pay for your own hardware instead of Command A's $2.5/$10 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume: Qwen3.6 35B A3B — At Open weight (self-host / free) it undercuts Command A, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Qwen3.6 35B A3B — Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs: Qwen3.6 35B A3B — 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 extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost: Qwen3.6 35B A3B — 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.
Qwen3.6 35B A3B: where it fits
A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. Released April 16, 2026 by Alibaba, it is built for extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost, runs at roughly 120 tokens per second on a single 24GB consumer GPU, apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN, and preserves its reasoning across turns, which cuts the overhead of agentic loops.
Its trade-offs: loses to its smaller dense sibling Qwen3.6 27B on every coding benchmark, despite more total parameters, its SWE-Bench score comes from Alibaba's internal scaffold rather than the standard public harness, and all 35B parameters must stay resident in VRAM even though only 3B compute per token. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
The defining split here is open vs. closed. Qwen3.6 35B A3B 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 Qwen3.6 35B A3B 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 Qwen3.6 35B A3B leans toward extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or Qwen3.6 35B A3B?
Qwen3.6 35B A3B 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?
Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Command A and Qwen3.6 35B A3B together?
Yes — a multi-model platform like LumiChats gives you Command A, Qwen3.6 35B A3B 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 Qwen3.6 35B A3B?
Qwen3.6 35B A3B — released April 16, 2026, about 14 months after Command A.
Command A vs Qwen3.6 35B A3B
Cohere · Global | Alibaba · China · Updated June 2026
Quick verdict
Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. Pick Qwen3.6 35B A3B for extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost or runs at roughly 120 tokens per second on a single 24gb consumer gpu. Choose Qwen3.6 35B A3B if you need self-hosting or data privacy; Command A if you want a managed API.
Command A (Cohere) and Qwen3.6 35B A3B (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. Qwen3.6 35B A3B is a sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. 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
▸Cost model: Qwen3.6 35B A3B ships open weights you can self-host (hardware cost only, no per-token fee), while Command A is API-metered at $2.5/$10 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: 256K vs 256K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: Qwen3.6 35B A3B is the newer model by about 14 months (released April 16, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Command A
Qwen3.6 35B A3B
Provider
Cohere (Global)
Alibaba (China)
Released
March 2025
April 16, 2026
Context window
256K (~384 pages)
256K (~393 pages)
Price (in/out)
$2.5/$10 per 1M tokens
Open weight (self-host / free)
Open weight?
No — API only
Yes — self-hostable
Modalities
text, code
text, image, code
SWE-Bench Verified
Not published
73.4%
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; Qwen3.6 35B A3B does not.
Strong long-context retrieval accuracy
Command A
Command A lists strong long-context retrieval accuracy among its strengths; Qwen3.6 35B A3B does not.
Multilingual
Command A
Command A lists multilingual among its strengths; Qwen3.6 35B A3B does not.
Extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost
Qwen3.6 35B A3B
A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware — and its weights are open while Command A is API-only.
Runs at roughly 120 tokens per second on a single 24GB consumer GPU
Qwen3.6 35B A3B
Command A is comparatively weak here — less consumer presence
Apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN
Qwen3.6 35B A3B
A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware — and it is the newer of the two.
Lowest cost at scale
Qwen3.6 35B A3B
Its weights are open, so at volume you pay for your own hardware instead of Command A's $2.5/$10 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen3.6 35B A3B
At Open weight (self-host / free) it undercuts Command A, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Qwen3.6 35B A3B
Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Qwen3.6 35B A3B
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 extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost
→ Qwen3.6 35B A3B
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.
Qwen3.6 35B A3B: where it fits
A sparse 35B mixture-of-experts running on 3B active parameters — strong agentic coding at near-3B cost on consumer hardware. Released April 16, 2026 by Alibaba, it is built for extreme sparsity — only 3B of 35B parameters active per token, giving near-3B inference cost, runs at roughly 120 tokens per second on a single 24GB consumer GPU, apache 2.0 weights with a 256K native context, extensible to about 1M via YaRN, and preserves its reasoning across turns, which cuts the overhead of agentic loops.
Its trade-offs: loses to its smaller dense sibling Qwen3.6 27B on every coding benchmark, despite more total parameters, its SWE-Bench score comes from Alibaba's internal scaffold rather than the standard public harness, and all 35B parameters must stay resident in VRAM even though only 3B compute per token. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
The defining split here is open vs. closed. Qwen3.6 35B A3B 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 Qwen3.6 35B A3B 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 Command A or Qwen3.6 35B A3B 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 Qwen3.6 35B A3B leans toward extreme sparsity — only 3b of 35b parameters active per token, giving near-3b inference cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or Qwen3.6 35B A3B?
Qwen3.6 35B A3B 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?
Effectively neither — 256K vs 256K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Command A and Qwen3.6 35B A3B together?
Yes — a multi-model platform like LumiChats gives you Command A, Qwen3.6 35B A3B 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 Qwen3.6 35B A3B?
Qwen3.6 35B A3B — released April 16, 2026, about 14 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.