Pick DeepSeek V4-Flash for exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens or mit-licensed open weights — free to self-host or run via a western host. 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 DeepSeek V4-Flash if you need self-hosting or data privacy; Fugu Ultra v2.0 if you want a managed API.
DeepSeek V4-Flash (DeepSeek) and Fugu Ultra v2.0 (Sakana AI) are two of the models people most often weigh against each other in 2026. DeepSeek V4-Flash is deepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens. 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 and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: DeepSeek V4-Flash is about 23× cheaper on input ($0.22/$0.66 per 1M tokens vs $5/$30 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
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 Ultra v2.0 is the newer model by about 41 days (released September 10, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
DeepSeek V4-Flash
Fugu Ultra v2.0
Provider
DeepSeek (China)
Sakana AI (Global)
Released
July 31, 2026
September 10, 2026
Context window
1M (~1,500 pages)
1M tokens (~1,500 pages)
Price (in/out)
$0.22/$0.66 per 1M tokens
$5/$30 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
Exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens: DeepSeek V4-Flash — At $0.22/$0.66 per 1M tokens it undercuts Fugu Ultra v2.0 ($5/$30 per 1M tokens), and that gap compounds at volume.
MIT-licensed open weights — free to self-host or run via a Western host: DeepSeek V4-Flash — Open weights make this possible at all — Fugu Ultra v2.0 is API-only, so it cannot leave the vendor's servers.
1M-token context window: DeepSeek V4-Flash — Fugu Ultra v2.0 is comparatively weak here — pricing rises to roughly $10/$45 per million tokens for prompts above 272K tokens
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 — DeepSeek V4-Flash is comparatively weak here — coding/agentic figures like Terminal-Bench 82.7 are DeepSeek's own, not independently reproduced
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 — DeepSeek V4-Flash is comparatively weak here — below the top frontier models on overall intelligence
1M-token context window: 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 is the newer of the two.
Lowest cost at scale: DeepSeek V4-Flash — At $0.22/$0.66 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-Flash — At $0.22/$0.66 per 1M tokens it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: DeepSeek V4-Flash — Open weights let you run it on your own hardware; Fugu Ultra v2.0 is API-only.
Anyone whose priority is exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens: DeepSeek V4-Flash — 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.
DeepSeek V4-Flash: where it fits
DeepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens. Released July 31, 2026 by DeepSeek, it is built for exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens, mIT-licensed open weights — free to self-host or run via a Western host, 1M-token context window, and strong coding and agentic performance for the price (DeepSeek reports 82.7 on Terminal-Bench 2.1).
Its trade-offs are real: coding/agentic figures like Terminal-Bench 82.7 are DeepSeek's own, not independently reproduced, text and code focused — not a full multimodal model, deepSeek's own hosted API stores data in China; self-host or use a Western host for privacy, and below the top frontier models on overall intelligence. At $0.22 in / $0.66 out per million tokens, it sits in the budget price band.
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. DeepSeek V4-Flash 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.
Frequently asked questions
Is DeepSeek V4-Flash 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, DeepSeek V4-Flash leans toward exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens 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, DeepSeek V4-Flash or Fugu Ultra v2.0?
DeepSeek V4-Flash 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek V4-Flash and Fugu Ultra v2.0 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Flash, 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, DeepSeek V4-Flash or Fugu Ultra v2.0?
Fugu Ultra v2.0 — released September 10, 2026, about 41 days after DeepSeek V4-Flash.
DeepSeek V4-Flash vs Fugu Ultra v2.0
DeepSeek · China | Sakana AI · Global · Updated June 2026
Quick verdict
Pick DeepSeek V4-Flash for exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens or mit-licensed open weights — free to self-host or run via a western host. 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 DeepSeek V4-Flash if you need self-hosting or data privacy; Fugu Ultra v2.0 if you want a managed API.
DeepSeek V4-Flash (DeepSeek) and Fugu Ultra v2.0 (Sakana AI) are two of the models people most often weigh against each other in 2026. DeepSeek V4-Flash is deepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens. 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 and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: DeepSeek V4-Flash is about 23× cheaper on input ($0.22/$0.66 per 1M tokens vs $5/$30 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸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 Ultra v2.0 is the newer model by about 41 days (released September 10, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
DeepSeek V4-Flash
Fugu Ultra v2.0
Provider
DeepSeek (China)
Sakana AI (Global)
Released
July 31, 2026
September 10, 2026
Context window
1M (~1,500 pages)
1M tokens (~1,500 pages)
Price (in/out)
$0.22/$0.66 per 1M tokens
$5/$30 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
Exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens
DeepSeek V4-Flash
At $0.22/$0.66 per 1M tokens it undercuts Fugu Ultra v2.0 ($5/$30 per 1M tokens), and that gap compounds at volume.
MIT-licensed open weights — free to self-host or run via a Western host
DeepSeek V4-Flash
Open weights make this possible at all — Fugu Ultra v2.0 is API-only, so it cannot leave the vendor's servers.
1M-token context window
DeepSeek V4-Flash
Fugu Ultra v2.0 is comparatively weak here — pricing rises to roughly $10/$45 per million tokens for prompts above 272K tokens
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
DeepSeek V4-Flash is comparatively weak here — coding/agentic figures like Terminal-Bench 82.7 are DeepSeek's own, not independently reproduced
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
DeepSeek V4-Flash is comparatively weak here — below the top frontier models on overall intelligence
1M-token context window
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 is the newer of the two.
Lowest cost at scale
DeepSeek V4-Flash
At $0.22/$0.66 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-Flash
At $0.22/$0.66 per 1M tokens it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ DeepSeek V4-Flash
Open weights let you run it on your own hardware; Fugu Ultra v2.0 is API-only.
Anyone whose priority is exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens
→ DeepSeek V4-Flash
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.
DeepSeek V4-Flash: where it fits
DeepSeek's MIT-licensed open-weight model — arguably the best value-per-intelligence available, scoring 52 on the independent AA Index at just $0.14/$0.28 per million tokens. Released July 31, 2026 by DeepSeek, it is built for exceptional value — Artificial Analysis Intelligence Index 52 at just $0.14/$0.28 per million tokens, mIT-licensed open weights — free to self-host or run via a Western host, 1M-token context window, and strong coding and agentic performance for the price (DeepSeek reports 82.7 on Terminal-Bench 2.1).
Its trade-offs are real: coding/agentic figures like Terminal-Bench 82.7 are DeepSeek's own, not independently reproduced, text and code focused — not a full multimodal model, deepSeek's own hosted API stores data in China; self-host or use a Western host for privacy, and below the top frontier models on overall intelligence. At $0.22 in / $0.66 out per million tokens, it sits in the budget price band.
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. DeepSeek V4-Flash 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 DeepSeek V4-Flash 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.
Is DeepSeek V4-Flash 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, DeepSeek V4-Flash leans toward exceptional value — artificial analysis intelligence index 52 at just $0.14/$0.28 per million tokens 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, DeepSeek V4-Flash or Fugu Ultra v2.0?
DeepSeek V4-Flash 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both DeepSeek V4-Flash and Fugu Ultra v2.0 together?
Yes — a multi-model platform like LumiChats gives you DeepSeek V4-Flash, 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, DeepSeek V4-Flash or Fugu Ultra v2.0?
Fugu Ultra v2.0 — released September 10, 2026, about 41 days after DeepSeek V4-Flash.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.