Pick DeepSeek R1 for open-weight reasoning model or transparent chain-of-thought. Pick Fugu Max for cost-efficient multi-agent orchestration — undercuts claude sonnet 5 and kimi k3 on output cost by a claimed 40-60% or 1m-token context window at $2/$6 per million tokens. Choose DeepSeek R1 if you need self-hosting or data privacy; Fugu Max if you want a managed API.
DeepSeek R1 (DeepSeek) and Fugu Max (Sakana AI) are two of the models people most often weigh against each other in 2026. DeepSeek R1 is the open-weight reasoning model that reset price expectations in early 2025. Fugu Max is sakana AI's cost-first multi-agent orchestration model — not a single trained model, but a routed pool of models behind one API, priced at $2/$6 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
Price: DeepSeek R1 is about 3.6× cheaper on input ($0.55/$2.19 per 1M tokens vs $2/$6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Fugu Max holds 7.8× more — 1M tokens (~1,500 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Fugu Max is the newer model by about 20 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
DeepSeek R1
Fugu Max
Provider
DeepSeek (China)
Sakana AI (Global)
Released
January 2025
September 10, 2026
Context window
128K (~192 pages)
1M tokens (~1,500 pages)
Price (in/out)
$0.55/$2.19 per 1M tokens
$2/$6 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Open-weight reasoning model: DeepSeek R1 — Open weights make this possible at all — Fugu Max is API-only, so it cannot leave the vendor's servers.
Transparent chain-of-thought: DeepSeek R1 — The open-weight reasoning model that reset price expectations in early 2025 — and it runs cheaper at $0.55/$2.19 per 1M tokens.
Low cost: DeepSeek R1 — At $0.55/$2.19 per 1M tokens it undercuts Fugu Max ($2/$6 per 1M tokens), and that gap compounds at volume.
Cost-efficient multi-agent orchestration — undercuts Claude Sonnet 5 and Kimi K3 on output cost by a claimed 40-60%: Fugu Max — Sakana AI's cost-first multi-agent orchestration model — not a single trained model, but a routed pool of models behind one API, priced at $2/$6 per million tokens — and it carries the larger 1M tokens context.
1M-token context window at $2/$6 per million tokens: Fugu Max — Its 1M tokens window holds about 7.8× more than DeepSeek R1's 128K in a single prompt.
OpenAI-compatible API — drop-in replacement for single-model integrations: Fugu Max — DeepSeek R1 is comparatively weak here — discontinued - no longer offered as a standalone model via DeepSeek's API as of mid-2026; the legacy alias that used to point to it stopped working July 24, 2026
Lowest cost at scale: DeepSeek R1 — At $0.55/$2.19 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Fugu Max — Its 1M tokens window is about 7.8× larger than DeepSeek R1's 128K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: DeepSeek R1 — At $0.55/$2.19 per 1M tokens it undercuts Fugu Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Fugu Max — Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs: DeepSeek R1 — Open weights let you run it on your own hardware; Fugu Max is API-only.
Anyone whose priority is open-weight reasoning model: DeepSeek R1 — It is specifically built for that.
Anyone whose priority is cost-efficient multi-agent orchestration — undercuts claude sonnet 5 and kimi k3 on output cost by a claimed 40-60%: Fugu Max — That is its strongest area.
DeepSeek R1: where it fits
The open-weight reasoning model that reset price expectations in early 2025. Released January 2025 by DeepSeek, it is built for open-weight reasoning model, transparent chain-of-thought, low cost, and strong maths and code.
Its trade-offs are real: discontinued - no longer offered as a standalone model via DeepSeek's API as of mid-2026; the legacy alias that used to point to it stopped working July 24, 2026, older than V4, smaller 128K context, and text/code focused. At $0.55 in / $2.19 out per million tokens, it sits in the budget price band.
Fugu Max: where it fits
Sakana AI's cost-first multi-agent orchestration model — not a single trained model, but a routed pool of models behind one API, priced at $2/$6 per million tokens. Released September 10, 2026 by Sakana AI, it is built for cost-efficient multi-agent orchestration — undercuts Claude Sonnet 5 and Kimi K3 on output cost by a claimed 40-60%, 1M-token context window at $2/$6 per million tokens, and openAI-compatible API — drop-in replacement for single-model integrations.
Its trade-offs: not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that routes tasks across a pool of other models, so raw benchmark comparisons to monolithic models can be misleading, the cheaper sibling to Fugu Ultra v2 — lower ceiling on the hardest reasoning tasks, and a young, first-generation product from Sakana AI's orchestration approach, unproven at scale versus established frontier labs. At $2 in / $6 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. DeepSeek R1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Fugu Max 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 DeepSeek R1 or Fugu Max 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, DeepSeek R1 leans toward open-weight reasoning model while Fugu Max leans toward cost-efficient multi-agent orchestration — undercuts claude sonnet 5 and kimi k3 on output cost by a claimed 40-60%, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek R1 or Fugu Max?
DeepSeek R1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Fugu Max is API-metered at $2/$6 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 Max — 1M tokens vs 128K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both DeepSeek R1 and Fugu Max together?
Yes — a multi-model platform like LumiChats gives you DeepSeek R1, Fugu Max 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, DeepSeek R1 or Fugu Max?
Fugu Max — released September 10, 2026, about 20 months after DeepSeek R1.
DeepSeek R1 vs Fugu Max
DeepSeek · China | Sakana AI · Global · Updated June 2026
Quick verdict
Pick DeepSeek R1 for open-weight reasoning model or transparent chain-of-thought. Pick Fugu Max for cost-efficient multi-agent orchestration — undercuts claude sonnet 5 and kimi k3 on output cost by a claimed 40-60% or 1m-token context window at $2/$6 per million tokens. Choose DeepSeek R1 if you need self-hosting or data privacy; Fugu Max if you want a managed API.
DeepSeek R1 (DeepSeek) and Fugu Max (Sakana AI) are two of the models people most often weigh against each other in 2026. DeepSeek R1 is the open-weight reasoning model that reset price expectations in early 2025. Fugu Max is sakana AI's cost-first multi-agent orchestration model — not a single trained model, but a routed pool of models behind one API, priced at $2/$6 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
▸Price: DeepSeek R1 is about 3.6× cheaper on input ($0.55/$2.19 per 1M tokens vs $2/$6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Fugu Max holds 7.8× more — 1M tokens (~1,500 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Fugu Max is the newer model by about 20 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
DeepSeek R1
Fugu Max
Provider
DeepSeek (China)
Sakana AI (Global)
Released
January 2025
September 10, 2026
Context window
128K (~192 pages)
1M tokens (~1,500 pages)
Price (in/out)
$0.55/$2.19 per 1M tokens
$2/$6 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Open-weight reasoning model
DeepSeek R1
Open weights make this possible at all — Fugu Max is API-only, so it cannot leave the vendor's servers.
Transparent chain-of-thought
DeepSeek R1
The open-weight reasoning model that reset price expectations in early 2025 — and it runs cheaper at $0.55/$2.19 per 1M tokens.
Low cost
DeepSeek R1
At $0.55/$2.19 per 1M tokens it undercuts Fugu Max ($2/$6 per 1M tokens), and that gap compounds at volume.
Cost-efficient multi-agent orchestration — undercuts Claude Sonnet 5 and Kimi K3 on output cost by a claimed 40-60%
Fugu Max
Sakana AI's cost-first multi-agent orchestration model — not a single trained model, but a routed pool of models behind one API, priced at $2/$6 per million tokens — and it carries the larger 1M tokens context.
1M-token context window at $2/$6 per million tokens
Fugu Max
Its 1M tokens window holds about 7.8× more than DeepSeek R1's 128K in a single prompt.
OpenAI-compatible API — drop-in replacement for single-model integrations
Fugu Max
DeepSeek R1 is comparatively weak here — discontinued - no longer offered as a standalone model via DeepSeek's API as of mid-2026; the legacy alias that used to point to it stopped working July 24, 2026
Lowest cost at scale
DeepSeek R1
At $0.55/$2.19 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Fugu Max
Its 1M tokens window is about 7.8× larger than DeepSeek R1's 128K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ DeepSeek R1
At $0.55/$2.19 per 1M tokens it undercuts Fugu Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Fugu Max
Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ DeepSeek R1
Open weights let you run it on your own hardware; Fugu Max is API-only.
Anyone whose priority is open-weight reasoning model
→ DeepSeek R1
It is specifically built for that.
Anyone whose priority is cost-efficient multi-agent orchestration — undercuts claude sonnet 5 and kimi k3 on output cost by a claimed 40-60%
→ Fugu Max
That is its strongest area.
DeepSeek R1: where it fits
The open-weight reasoning model that reset price expectations in early 2025. Released January 2025 by DeepSeek, it is built for open-weight reasoning model, transparent chain-of-thought, low cost, and strong maths and code.
Its trade-offs are real: discontinued - no longer offered as a standalone model via DeepSeek's API as of mid-2026; the legacy alias that used to point to it stopped working July 24, 2026, older than V4, smaller 128K context, and text/code focused. At $0.55 in / $2.19 out per million tokens, it sits in the budget price band.
Fugu Max: where it fits
Sakana AI's cost-first multi-agent orchestration model — not a single trained model, but a routed pool of models behind one API, priced at $2/$6 per million tokens. Released September 10, 2026 by Sakana AI, it is built for cost-efficient multi-agent orchestration — undercuts Claude Sonnet 5 and Kimi K3 on output cost by a claimed 40-60%, 1M-token context window at $2/$6 per million tokens, and openAI-compatible API — drop-in replacement for single-model integrations.
Its trade-offs: not a single trained model — Sakana describes Fugu as "a Multi-Agent System, Delivered as One Model" that routes tasks across a pool of other models, so raw benchmark comparisons to monolithic models can be misleading, the cheaper sibling to Fugu Ultra v2 — lower ceiling on the hardest reasoning tasks, and a young, first-generation product from Sakana AI's orchestration approach, unproven at scale versus established frontier labs. At $2 in / $6 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. DeepSeek R1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Fugu Max 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 DeepSeek R1 and Fugu Max 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, DeepSeek R1 leans toward open-weight reasoning model while Fugu Max leans toward cost-efficient multi-agent orchestration — undercuts claude sonnet 5 and kimi k3 on output cost by a claimed 40-60%, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, DeepSeek R1 or Fugu Max?
DeepSeek R1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Fugu Max is API-metered at $2/$6 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 Max — 1M tokens vs 128K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both DeepSeek R1 and Fugu Max together?
Yes — a multi-model platform like LumiChats gives you DeepSeek R1, Fugu Max 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, DeepSeek R1 or Fugu Max?
Fugu Max — released September 10, 2026, about 20 months after DeepSeek R1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.