Pick DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable or 1m-token context with up to 384k output tokens. 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 V4-Pro if you need self-hosting or data privacy; Fugu Max if you want a managed API.
DeepSeek V4-Pro (DeepSeek) and Fugu Max (Sakana AI) are two of the models people most often weigh against each other in 2026. DeepSeek V4-Pro is deepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. 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 and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: DeepSeek V4-Pro is about 3× cheaper on input ($0.66/$1.98 per 1M tokens vs $2/$6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: Fugu Max is the newer model by about 5 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
DeepSeek V4-Pro
Fugu Max
Provider
DeepSeek (China)
Sakana AI (Global)
Released
April 24, 2026
September 10, 2026
Context window
1M (~1,500 pages)
1M tokens (~1,500 pages)
Price (in/out)
$0.66/$1.98 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 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable: DeepSeek V4-Pro — Open weights make this possible at all — Fugu Max is API-only, so it cannot leave the vendor's servers.
1M-token context with up to 384K output tokens: DeepSeek V4-Pro — DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it runs cheaper at $0.66/$1.98 per 1M tokens.
Permanent low pricing at $0.435/$0.87 per million, set May 2026: DeepSeek V4-Pro — DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and its weights are open while Fugu Max is API-only.
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 is the newer of the two.
1M-token context window at $2/$6 per million tokens: Fugu Max — Fugu Max lists 1M-token context window at $2/$6 per million tokens among its strengths; DeepSeek V4-Pro does not.
OpenAI-compatible API — drop-in replacement for single-model integrations: Fugu Max — Fugu Max lists openAI-compatible API — drop-in replacement for single-model integrations among its strengths; DeepSeek V4-Pro does not.
Lowest cost at scale: DeepSeek V4-Pro — At $0.66/$1.98 per 1M tokens, 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: DeepSeek V4-Pro — At $0.66/$1.98 per 1M tokens it undercuts Fugu Max, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: DeepSeek V4-Pro — Open weights let you run it on your own hardware; Fugu Max is API-only.
Anyone whose priority is open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable: DeepSeek V4-Pro — 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 V4-Pro: where it fits
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Released April 24, 2026 by DeepSeek, it is built for open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable, 1M-token context with up to 384K output tokens, permanent low pricing at $0.435/$0.87 per million, set May 2026, and sources place it near the top of open-weight coding, around 80 on SWE-Bench Verified.
Its trade-offs are real: independent SWE-Bench Verified placement is inconsistent across sources, pro and Pro-Max variants are quoted with different scores, text and code only — no image, audio or video, and overlaps DeepSeek V4 and V3.2 already in this comparison. At $0.66 in / $1.98 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 V4-Pro 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 V4-Pro 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 V4-Pro leans toward open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable 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 V4-Pro or Fugu Max?
DeepSeek V4-Pro 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek V4-Pro and Fugu Max together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Pro, 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 V4-Pro or Fugu Max?
Fugu Max — released September 10, 2026, about 5 months after DeepSeek V4-Pro.
DeepSeek V4-Pro vs Fugu Max
DeepSeek · China | Sakana AI · Global · Updated June 2026
Quick verdict
Pick DeepSeek V4-Pro for open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable or 1m-token context with up to 384k output tokens. 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 V4-Pro if you need self-hosting or data privacy; Fugu Max if you want a managed API.
DeepSeek V4-Pro (DeepSeek) and Fugu Max (Sakana AI) are two of the models people most often weigh against each other in 2026. DeepSeek V4-Pro is deepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. 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 and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: DeepSeek V4-Pro is about 3× cheaper on input ($0.66/$1.98 per 1M tokens vs $2/$6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: Fugu Max is the newer model by about 5 months (released September 10, 2026), usually meaning fresher training data and capabilities.
Open weights make this possible at all — Fugu Max is API-only, so it cannot leave the vendor's servers.
1M-token context with up to 384K output tokens
DeepSeek V4-Pro
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and it runs cheaper at $0.66/$1.98 per 1M tokens.
Permanent low pricing at $0.435/$0.87 per million, set May 2026
DeepSeek V4-Pro
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices — and its weights are open while Fugu Max is API-only.
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 is the newer of the two.
1M-token context window at $2/$6 per million tokens
Fugu Max
Fugu Max lists 1M-token context window at $2/$6 per million tokens among its strengths; DeepSeek V4-Pro does not.
OpenAI-compatible API — drop-in replacement for single-model integrations
Fugu Max
Fugu Max lists openAI-compatible API — drop-in replacement for single-model integrations among its strengths; DeepSeek V4-Pro does not.
Lowest cost at scale
DeepSeek V4-Pro
At $0.66/$1.98 per 1M tokens, 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
→ DeepSeek V4-Pro
At $0.66/$1.98 per 1M tokens it undercuts Fugu Max, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ DeepSeek V4-Pro
Open weights let you run it on your own hardware; Fugu Max is API-only.
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 V4-Pro: where it fits
DeepSeek's 1.6-trillion-parameter open-weight model at $0.435/$0.87 — strong open-weight coding and a 1M context at a fraction of flagship prices. Released April 24, 2026 by DeepSeek, it is built for open-weight 1.6T MoE (~49B active) — DeepSeek's largest, self-hostable, 1M-token context with up to 384K output tokens, permanent low pricing at $0.435/$0.87 per million, set May 2026, and sources place it near the top of open-weight coding, around 80 on SWE-Bench Verified.
Its trade-offs are real: independent SWE-Bench Verified placement is inconsistent across sources, pro and Pro-Max variants are quoted with different scores, text and code only — no image, audio or video, and overlaps DeepSeek V4 and V3.2 already in this comparison. At $0.66 in / $1.98 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 V4-Pro 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 V4-Pro 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 V4-Pro leans toward open-weight 1.6t moe (~49b active) — deepseek's largest, self-hostable 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 V4-Pro or Fugu Max?
DeepSeek V4-Pro 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek V4-Pro and Fugu Max together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Pro, 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 V4-Pro or Fugu Max?
Fugu Max — released September 10, 2026, about 5 months after DeepSeek V4-Pro.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.