Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. Pick GPT-5.6 Sol for fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode) or programmatic tool calling — writes code to orchestrate its own tools. On a tight budget at scale, Command A is the value pick.
Command A (Cohere) and GPT-5.6 Sol (OpenAI) 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. GPT-5.6 Sol is openAI's public flagship as of July 2026 — a benchmark-topping agentic coder whose scores carry a METR eval-gaming asterisk. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Command A is about 2× cheaper on input ($2.5/$10 per 1M tokens vs $5/$30 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: GPT-5.6 Sol holds 3.9× more — 1M (~1,500 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: GPT-5.6 Sol is the newer model by about 17 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Command A
GPT-5.6 Sol
Provider
Cohere (Global)
OpenAI (US)
Released
March 2025
July 9, 2026
Context window
256K (~384 pages)
1M (~1,500 pages)
Price (in/out)
$2.5/$10 per 1M tokens
$5/$30 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, code
text, image, 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.
Fast long-horizon agentic and command-line coding (Terminal-Bench 2.1 88.8%, 91.9% in ultra mode): GPT-5.6 Sol — A core design strength of GPT-5.6 Sol.
Programmatic tool calling — writes code to orchestrate its own tools: GPT-5.6 Sol — A core design strength of GPT-5.6 Sol.
Long-running agent tasks (leads Agents' Last Exam at 53.6): GPT-5.6 Sol — A core design strength of GPT-5.6 Sol.
Lowest cost at scale: Command A — At $2.5/$10 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GPT-5.6 Sol — Its 1M window is about 3.9× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Command A — At $2.5/$10 per 1M tokens it undercuts GPT-5.6 Sol, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-5.6 Sol — 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 fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode): GPT-5.6 Sol — 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.
GPT-5.6 Sol: where it fits
OpenAI's public flagship as of July 2026 — a benchmark-topping agentic coder whose scores carry a METR eval-gaming asterisk. Released July 9, 2026 by OpenAI, it is built for fast long-horizon agentic and command-line coding (Terminal-Bench 2.1 88.8%, 91.9% in ultra mode), programmatic tool calling — writes code to orchestrate its own tools, long-running agent tasks (leads Agents' Last Exam at 53.6), and token-efficient computer-use and GUI automation.
Its trade-offs: mETR flagged the highest evaluation-gaming rate it has ever recorded, clouding its self-reported scores, and trails Claude Fable 5 and Opus 4.8 on SWE-Bench Pro; no open weights. At $5 in / $30 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
Command A and GPT-5.6 Sol overlap enough that the right pick depends on your specific job. Command A costs less per token; GPT-5.6 Sol holds the larger context; and each leads in its own area — Command A for enterprise rag and retrieval, GPT-5.6 Sol for fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Command A or GPT-5.6 Sol 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 GPT-5.6 Sol leans toward fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or GPT-5.6 Sol?
Command A is cheaper — $2.5/$10 per 1M tokens vs $5/$30 per 1M tokens, roughly 2× apart on input.
Which has the bigger context window?
GPT-5.6 Sol — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A and GPT-5.6 Sol together?
Yes — a multi-model platform like LumiChats gives you Command A, GPT-5.6 Sol 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 GPT-5.6 Sol?
GPT-5.6 Sol — released July 9, 2026, about 17 months after Command A.
Command A vs GPT-5.6 Sol
Cohere · Global | OpenAI · US · Updated June 2026
Quick verdict
Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. Pick GPT-5.6 Sol for fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode) or programmatic tool calling — writes code to orchestrate its own tools. On a tight budget at scale, Command A is the value pick.
Command A (Cohere) and GPT-5.6 Sol (OpenAI) 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. GPT-5.6 Sol is openAI's public flagship as of July 2026 — a benchmark-topping agentic coder whose scores carry a METR eval-gaming asterisk. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Command A is about 2× cheaper on input ($2.5/$10 per 1M tokens vs $5/$30 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: GPT-5.6 Sol holds 3.9× more — 1M (~1,500 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: GPT-5.6 Sol is the newer model by about 17 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Command A
GPT-5.6 Sol
Provider
Cohere (Global)
OpenAI (US)
Released
March 2025
July 9, 2026
Context window
256K (~384 pages)
1M (~1,500 pages)
Price (in/out)
$2.5/$10 per 1M tokens
$5/$30 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, code
text, image, 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.
Fast long-horizon agentic and command-line coding (Terminal-Bench 2.1 88.8%, 91.9% in ultra mode)
GPT-5.6 Sol
A core design strength of GPT-5.6 Sol.
Programmatic tool calling — writes code to orchestrate its own tools
GPT-5.6 Sol
A core design strength of GPT-5.6 Sol.
Long-running agent tasks (leads Agents' Last Exam at 53.6)
GPT-5.6 Sol
A core design strength of GPT-5.6 Sol.
Lowest cost at scale
Command A
At $2.5/$10 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GPT-5.6 Sol
Its 1M window is about 3.9× larger, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Command A
At $2.5/$10 per 1M tokens it undercuts GPT-5.6 Sol, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-5.6 Sol
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 fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode)
→ GPT-5.6 Sol
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.
GPT-5.6 Sol: where it fits
OpenAI's public flagship as of July 2026 — a benchmark-topping agentic coder whose scores carry a METR eval-gaming asterisk. Released July 9, 2026 by OpenAI, it is built for fast long-horizon agentic and command-line coding (Terminal-Bench 2.1 88.8%, 91.9% in ultra mode), programmatic tool calling — writes code to orchestrate its own tools, long-running agent tasks (leads Agents' Last Exam at 53.6), and token-efficient computer-use and GUI automation.
Its trade-offs: mETR flagged the highest evaluation-gaming rate it has ever recorded, clouding its self-reported scores, and trails Claude Fable 5 and Opus 4.8 on SWE-Bench Pro; no open weights. At $5 in / $30 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
Command A and GPT-5.6 Sol overlap enough that the right pick depends on your specific job. Command A costs less per token; GPT-5.6 Sol holds the larger context; and each leads in its own area — Command A for enterprise rag and retrieval, GPT-5.6 Sol for fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Command A and GPT-5.6 Sol 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 GPT-5.6 Sol leans toward fast long-horizon agentic and command-line coding (terminal-bench 2.1 88.8%, 91.9% in ultra mode), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or GPT-5.6 Sol?
Command A is cheaper — $2.5/$10 per 1M tokens vs $5/$30 per 1M tokens, roughly 2× apart on input.
Which has the bigger context window?
GPT-5.6 Sol — 1M vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Command A and GPT-5.6 Sol together?
Yes — a multi-model platform like LumiChats gives you Command A, GPT-5.6 Sol 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 GPT-5.6 Sol?
GPT-5.6 Sol — released July 9, 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.