Command A vs Reflection Beam 1.0
Cohere · Global | Reflection AI · US · Updated June 2026
Quick verdict
Pick Command A for enterprise rag and retrieval or strong long-context retrieval accuracy. Pick Reflection Beam 1.0 for 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0 or reflection claims 3-4x less inference compute than rival models (vendor claim). On a tight budget at scale, Reflection Beam 1.0 is the value pick.
Command A (Cohere) and Reflection Beam 1.0 (Reflection AI) 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. Reflection Beam 1.0 is reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Context window: Reflection Beam 1.0 holds 3.9× more — 1M tokens (~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: Reflection Beam 1.0 is the newer model by about 20 months (released October 16, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Command A | Reflection Beam 1.0 |
|---|---|---|
| Provider | Cohere (Global) | Reflection AI (US) |
| Released | March 2025 | October 16, 2026 |
| Context window | 256K (~384 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $2.5/$10 per 1M tokens | Open weight (self-host / free) |
| Open weight? | Yes — self-hostable | 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
Command A lists enterprise RAG and retrieval among its strengths; Reflection Beam 1.0 does not.
Strong long-context retrieval accuracy
Command A
Command A lists strong long-context retrieval accuracy among its strengths; Reflection Beam 1.0 does not.
Multilingual
Command A
Command A lists multilingual among its strengths; Reflection Beam 1.0 does not.
501B-parameter sparse MoE (about 23B active per token) with weights on Hugging Face under Apache 2.0
Reflection Beam 1.0
Its 1M tokens window holds about 3.9× more than Command A's 256K in a single prompt.
Reflection claims 3-4x less inference compute than rival models (vendor claim)
Reflection Beam 1.0
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models — and it carries the larger 1M tokens context.
Fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task
Reflection Beam 1.0
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models — and it is the newer of the two.
Lowest cost at scale
Reflection Beam 1.0
Its weights are open, so at volume you pay for your own hardware instead of Command A's $2.5/$10 per 1M tokens.
Largest single-prompt input
Reflection Beam 1.0
Its 1M tokens window is about 3.9× larger than Command A's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Reflection Beam 1.0
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
→ Reflection Beam 1.0
Larger 1M tokens 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 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0
→ Reflection Beam 1.0
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.
Reflection Beam 1.0: where it fits
Reflection AI's first open-weight model - a 501B Apache 2.0 MoE announced October 5 with weights published October 16, 2026, pitched as a US alternative to Chinese open models. Released October 16, 2026 by Reflection AI, it is built for 501B-parameter sparse MoE (about 23B active per token) with weights on Hugging Face under Apache 2.0, reflection claims 3-4x less inference compute than rival models (vendor claim), fast and cheap to run: Artificial Analysis measured about 385 output tokens/sec and $0.12 per index task, and third-party hosts list it from $0.25/$1.00 per million tokens (Nebius, as of Oct 27); Reflection's own API is in free beta.
Its trade-offs: artificial Analysis Intelligence Index of 30, well below DeepSeek V4.1 Flash and GLM-5.3 (45), text-only input; some users report reasoning loops on long agent runs, self-hosting needs about 353 GB of GPU memory even at NVFP4, and kernels are CUDA-only for now, and headline benchmarks come from Reflection's own model card; independent evaluation was limited at launch. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
Command A and Reflection Beam 1.0 overlap enough that the right pick depends on your specific job. Reflection Beam 1.0 costs less per token; Reflection Beam 1.0 holds the larger context; and each leads in its own area — Command A for enterprise rag and retrieval, Reflection Beam 1.0 for 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Command A and Reflection Beam 1.0 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.
See pricingFrequently asked questions
Is Command A or Reflection Beam 1.0 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 Reflection Beam 1.0 leans toward 501b-parameter sparse moe (about 23b active per token) with weights on hugging face under apache 2.0, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Command A or Reflection Beam 1.0?
Reflection Beam 1.0 is cheaper — $2.5/$10 per 1M tokens vs Open weight (self-host / free).
Which has the bigger context window?
Reflection Beam 1.0 — 1M tokens 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 Reflection Beam 1.0 together?
Yes — a multi-model platform like LumiChats gives you Command A, Reflection Beam 1.0 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 Reflection Beam 1.0?
Reflection Beam 1.0 — released October 16, 2026, about 20 months after Command A.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.