Command A+ vs Fugu Ultra v2.0

Cohere · Canada  |  Sakana AI · Global · Updated June 2026

Quick verdict

Pick Command A+ for cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model or a 218b-total/25b-active moe released with open weights (apache 2.0) on hugging face. Pick Fugu Ultra v2.0 for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark or claims to outperform flagship models like gpt-6 astra and claude fable 5.1 despite its underlying orchestration pool reportedly excluding both of them. Choose Command A+ if you need self-hosting or data privacy; Fugu Ultra v2.0 if you want a managed API.

Command A+ (Cohere) and Fugu Ultra v2.0 (Sakana AI) are two of the models people most often weigh against each other in 2026. Command A+ is cohere's newer, leaner flagship - a 218B open-weight MoE tuned for efficiency (just two GPUs to run) and 48-language support. Fugu Ultra v2.0 is sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens. 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

Side-by-side specs

SpecCommand A+Fugu Ultra v2.0
ProviderCohere (Canada) Sakana AI (Global)
ReleasedMay 19, 2026 September 10, 2026
Context window256K (unconfirmed) (~384 pages) 1M tokens (~1,500 pages)
Price (in/out)Open weight (self-host / free) $5/$30 per 1M tokens
Open weight?Yes — self-hostable No — API only
Modalitiestext, code text
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Cohere's newer, more efficient flagship - runs on just two H100 GPUs, unusually lean for a 218B-parameter model

Command A+

Fugu Ultra v2.0 is comparatively weak here — not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that dynamically routes tasks across a pool of other models, so head-to-head benchmark framing against monolithic frontier models should be read skeptically

A 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face

Command A+

Open weights make this possible at all — Fugu Ultra v2.0 is API-only, so it cannot leave the vendor's servers.

Supports 48 languages, including all official EU languages

Command A+

Cohere's newer, leaner flagship - a 218B open-weight MoE tuned for efficiency (just two GPUs to run) and 48-language support — and its weights are open while Fugu Ultra v2.0 is API-only.

Sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the DeepSWE coding-repair benchmark

Fugu Ultra v2.0

Command A+ is comparatively weak here — newer release with less independent benchmark verification than established flagships

Claims to outperform flagship models like GPT-6 Astra and Claude Fable 5.1 despite its underlying orchestration pool reportedly excluding both of them

Fugu Ultra v2.0

Sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens — and it carries the larger 1M tokens context.

1M-token context window

Fugu Ultra v2.0

Its 1M tokens window holds about 3.9× more than Command A+'s 256K (unconfirmed) in a single prompt.

Lowest cost at scale

Command A+

Its weights are open, so at volume you pay for your own hardware instead of Fugu Ultra v2.0's $5/$30 per 1M tokens.

Largest single-prompt input

Fugu Ultra v2.0

Its 1M tokens window is about 3.9× larger than Command A+'s 256K (unconfirmed), fitting roughly 1,500 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

Command A+

At Open weight (self-host / free) it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

Fugu Ultra v2.0

Larger 1M tokens window fits more in one prompt.

A team with data-privacy or self-hosting needs

Command A+

Open weights let you run it on your own hardware; Fugu Ultra v2.0 is API-only.

Anyone whose priority is cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model

Command A+

It is specifically built for that.

Anyone whose priority is sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark

Fugu Ultra v2.0

That is its strongest area.

Command A+: where it fits

Cohere's newer, leaner flagship - a 218B open-weight MoE tuned for efficiency (just two GPUs to run) and 48-language support. Released May 19, 2026 by Cohere, it is built for cohere's newer, more efficient flagship - runs on just two H100 GPUs, unusually lean for a 218B-parameter model, a 218B-total/25B-active MoE released with open weights (Apache 2.0) on Hugging Face, supports 48 languages, including all official EU languages, and positioned by Cohere as its 'most efficient and performant model to date'.

Its trade-offs are real: no official context window or per-token price published yet - both are estimated/unavailable, newer release with less independent benchmark verification than established flagships, and enterprise/multilingual focus rather than topping general reasoning leaderboards. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

Fugu Ultra v2.0: where it fits

Sakana AI's flagship multi-agent orchestration model, claiming best-or-joint-best results on 5 of 8 self-reported benchmarks against monolithic frontier models — $5/$30 per million tokens. Released September 10, 2026 by Sakana AI, it is built for sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the DeepSWE coding-repair benchmark, claims to outperform flagship models like GPT-6 Astra and Claude Fable 5.1 despite its underlying orchestration pool reportedly excluding both of them, and 1M-token context window.

Its trade-offs: not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that dynamically routes tasks across a pool of other models, so head-to-head benchmark framing against monolithic frontier models should be read skeptically, pricing rises to roughly $10/$45 per million tokens for prompts above 272K tokens, and benchmark comparisons against GPT-6 Astra and Claude Fable 5.1 are Sakana's own self-reported figures, not independently verified head-to-head scores. At $5 in / $30 out per million tokens, it sits in the premium price band.

The bottom line for this matchup

The defining split here is open vs. closed. Command A+ gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Fugu Ultra v2.0 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 Fugu Ultra v2.0 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 pricing

Frequently asked questions

Is Command A+ or Fugu Ultra v2.0 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 cohere's newer, more efficient flagship - runs on just two h100 gpus, unusually lean for a 218b-parameter model while Fugu Ultra v2.0 leans toward sakana's own evaluation reports best-or-joint-best results on 5 of 8 benchmarks tested, including a 74.3 on the deepswe coding-repair benchmark, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Command A+ or Fugu Ultra v2.0?

Command A+ is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Fugu Ultra v2.0 is API-metered at $5/$30 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?

Fugu Ultra v2.0 — 1M tokens vs 256K (unconfirmed), 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 Fugu Ultra v2.0 together?

Yes — a multi-model platform like LumiChats gives you Command A+, Fugu Ultra v2.0 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 Fugu Ultra v2.0?

Fugu Ultra v2.0 — released September 10, 2026, about 4 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.