Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. Pick Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost or runs a 295b model at the cost of a 21b — only 21b parameters active per token. Choose Hunyuan Hy3 if you need self-hosting or data privacy; Command A if you want a managed API.
Command A (Cohere) and Hunyuan Hy3 (Tencent) 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. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Hunyuan Hy3 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: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: Hunyuan Hy3 is the newer model by about 16 months (released July 6, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Command A
Hunyuan Hy3
Provider
Cohere (Global)
Tencent (China)
Released
March 2025
July 6, 2026
Context window
256K (~384 pages)
256K (~384 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, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Enterprise RAG and retrieval: Command A — A core design strength of Command A.
Strong long-context retrieval accuracy: Command A — A core design strength of Command A.
Multilingual: Command A — A core design strength of Command A.
Frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost: Hunyuan Hy3 — A core design strength of Hunyuan Hy3.
Runs a 295B model at the cost of a 21B — only 21B parameters active per token: Hunyuan Hy3 — A core design strength of Hunyuan Hy3.
Clean, unrestricted Apache-2.0 license with no geographic carve-out: Hunyuan Hy3 — A core design strength of Hunyuan Hy3.
Lowest cost at scale: Hunyuan Hy3 — At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume: Hunyuan Hy3 — At Open weight (self-host / free) it undercuts Command A, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: Hunyuan Hy3 — 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 frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost: Hunyuan Hy3 — 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.
Hunyuan Hy3: where it fits
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Released July 6, 2026 by Tencent, it is built for frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost, runs a 295B model at the cost of a 21B — only 21B parameters active per token, clean, unrestricted Apache-2.0 license with no geographic carve-out, and broad day-one ecosystem support plus an FP8 checkpoint.
Its trade-offs: benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion, and the hosted API is China-jurisdiction, and self-hosting a 295B MoE still needs serious hardware. 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. Hunyuan Hy3 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 Hunyuan Hy3 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 Hunyuan Hy3 leans toward frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or Hunyuan Hy3?
Hunyuan Hy3 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?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Command A and Hunyuan Hy3 together?
Yes — a multi-model platform like LumiChats gives you Command A, Hunyuan Hy3 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 Hunyuan Hy3?
Hunyuan Hy3 — released July 6, 2026, about 16 months after Command A.
Command A vs Hunyuan Hy3
Cohere · Global | Tencent · China · Updated June 2026
Quick verdict
Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. Pick Hunyuan Hy3 for frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost or runs a 295b model at the cost of a 21b — only 21b parameters active per token. Choose Hunyuan Hy3 if you need self-hosting or data privacy; Command A if you want a managed API.
Command A (Cohere) and Hunyuan Hy3 (Tencent) 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. Hunyuan Hy3 is a 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: Hunyuan Hy3 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: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: Hunyuan Hy3 is the newer model by about 16 months (released July 6, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Command A
Hunyuan Hy3
Provider
Cohere (Global)
Tencent (China)
Released
March 2025
July 6, 2026
Context window
256K (~384 pages)
256K (~384 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, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Enterprise RAG and retrieval
Command A
A core design strength of Command A.
Strong long-context retrieval accuracy
Command A
A core design strength of Command A.
Multilingual
Command A
A core design strength of Command A.
Frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost
Hunyuan Hy3
A core design strength of Hunyuan Hy3.
Runs a 295B model at the cost of a 21B — only 21B parameters active per token
Hunyuan Hy3
A core design strength of Hunyuan Hy3.
Clean, unrestricted Apache-2.0 license with no geographic carve-out
Hunyuan Hy3
A core design strength of Hunyuan Hy3.
Lowest cost at scale
Hunyuan Hy3
At Open weight (self-host / free), it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Hunyuan Hy3
At Open weight (self-host / free) it undercuts Command A, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ Hunyuan Hy3
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 frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost
→ Hunyuan Hy3
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.
Hunyuan Hy3: where it fits
A 295B Apache-2.0 open MoE that reaches frontier reasoning quality while running at roughly 21B active-parameter cost. Released July 6, 2026 by Tencent, it is built for frontier-level reported reasoning and science (GPQA Diamond 90.4) at low active-parameter cost, runs a 295B model at the cost of a 21B — only 21B parameters active per token, clean, unrestricted Apache-2.0 license with no geographic carve-out, and broad day-one ecosystem support plus an FP8 checkpoint.
Its trade-offs: benchmarks are largely self-reported, and the ultra-low hosted pricing is a limited promotion, and the hosted API is China-jurisdiction, and self-hosting a 295B MoE still needs serious hardware. 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. Hunyuan Hy3 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 Hunyuan Hy3 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 Hunyuan Hy3 leans toward frontier-level reported reasoning and science (gpqa diamond 90.4) at low active-parameter cost, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or Hunyuan Hy3?
Hunyuan Hy3 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?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Command A and Hunyuan Hy3 together?
Yes — a multi-model platform like LumiChats gives you Command A, Hunyuan Hy3 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 Hunyuan Hy3?
Hunyuan Hy3 — released July 6, 2026, about 16 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.