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. Pick Gemini 3.7 Flash for strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing or 1m-token context with full multimodal input (text, image, audio, video). On a tight budget at scale, Gemini 3.7 Flash is the value pick.
Fugu Ultra v2.0 (Sakana AI) and Gemini 3.7 Flash (Google) are two of the models people most often weigh against each other in 2026. 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. Gemini 3.7 Flash is google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Gemini 3.7 Flash is about 6.7× cheaper on input ($0.75/$3.75 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: 1M tokens vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Recency: Fugu Ultra v2.0 is the newer model by about 28 days (released September 10, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Fugu Ultra v2.0
Gemini 3.7 Flash
Provider
Sakana AI (Global)
Google (US)
Released
September 10, 2026
August 13, 2026
Context window
1M tokens (~1,500 pages)
1M (~1,573 pages)
Price (in/out)
$5/$30 per 1M tokens
$0.75/$3.75 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text
text, image, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
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 — Gemini 3.7 Flash is comparatively weak here — trails GPT-5.6 Terra on the hardest repo-scale and terminal-agent coding
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 — Gemini 3.7 Flash is comparatively weak here — a fast 'workhorse,' not Google's top-intelligence model (Gemini 3.1 Pro is still the flagship)
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.
Strong intelligence-per-dollar - Artificial Analysis Intelligence Index 56 at introductory $0.75/$3.75 pricing: Gemini 3.7 Flash — Fugu Ultra v2.0 is comparatively weak here — pricing rises to roughly $10/$45 per million tokens for prompts above 272K tokens
1M-token context with full multimodal input (text, image, audio, video): Gemini 3.7 Flash — Google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed — and it runs cheaper at $0.75/$3.75 per 1M tokens.
Built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra: Gemini 3.7 Flash — Gemini 3.7 Flash lists built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra among its strengths; Fugu Ultra v2.0 does not.
Lowest cost at scale: Gemini 3.7 Flash — At $0.75/$3.75 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: Gemini 3.7 Flash — At $0.75/$3.75 per 1M tokens it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemini 3.7 Flash — Larger 1M window fits more in one prompt.
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 — It is specifically built for that.
Anyone whose priority is strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing: Gemini 3.7 Flash — That is its strongest area.
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 are real: 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.
Gemini 3.7 Flash: where it fits
Google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed. Released August 13, 2026 by Google, it is built for strong intelligence-per-dollar - Artificial Analysis Intelligence Index 56 at introductory $0.75/$3.75 pricing, 1M-token context with full multimodal input (text, image, audio, video), built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra, and wins broad-coding and web-development benchmarks against GPT-5.6 Terra.
Its trade-offs: introductory pricing ($0.75/$3.75) reverts to $1.50/$7.50 on Jan 1, 2027, trails GPT-5.6 Terra on the hardest repo-scale and terminal-agent coding, a fast 'workhorse,' not Google's top-intelligence model (Gemini 3.1 Pro is still the flagship), and some benchmark gains are Google's own figures. At $0.75 in / $3.75 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Fugu Ultra v2.0 and Gemini 3.7 Flash overlap enough that the right pick depends on your specific job. Gemini 3.7 Flash costs less per token; Gemini 3.7 Flash holds the larger context; and each leads in its own area — 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, Gemini 3.7 Flash for strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Fugu Ultra v2.0 or Gemini 3.7 Flash 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, 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 while Gemini 3.7 Flash leans toward strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Ultra v2.0 or Gemini 3.7 Flash?
Gemini 3.7 Flash is cheaper — $5/$30 per 1M tokens vs $0.75/$3.75 per 1M tokens, roughly 6.7× apart on input.
Which has the bigger context window?
Effectively neither — 1M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Fugu Ultra v2.0 and Gemini 3.7 Flash together?
Yes — a multi-model platform like LumiChats gives you Fugu Ultra v2.0, Gemini 3.7 Flash 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, Fugu Ultra v2.0 or Gemini 3.7 Flash?
Fugu Ultra v2.0 — released September 10, 2026, about 28 days after Gemini 3.7 Flash.
Fugu Ultra v2.0 vs Gemini 3.7 Flash
Sakana AI · Global | Google · US · Updated June 2026
Quick verdict
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. Pick Gemini 3.7 Flash for strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing or 1m-token context with full multimodal input (text, image, audio, video). On a tight budget at scale, Gemini 3.7 Flash is the value pick.
Fugu Ultra v2.0 (Sakana AI) and Gemini 3.7 Flash (Google) are two of the models people most often weigh against each other in 2026. 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. Gemini 3.7 Flash is google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Gemini 3.7 Flash is about 6.7× cheaper on input ($0.75/$3.75 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: 1M tokens vs 1M — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Recency: Fugu Ultra v2.0 is the newer model by about 28 days (released September 10, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Fugu Ultra v2.0
Gemini 3.7 Flash
Provider
Sakana AI (Global)
Google (US)
Released
September 10, 2026
August 13, 2026
Context window
1M tokens (~1,500 pages)
1M (~1,573 pages)
Price (in/out)
$5/$30 per 1M tokens
$0.75/$3.75 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text
text, image, audio, video, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
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
Gemini 3.7 Flash is comparatively weak here — trails GPT-5.6 Terra on the hardest repo-scale and terminal-agent coding
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
Gemini 3.7 Flash is comparatively weak here — a fast 'workhorse,' not Google's top-intelligence model (Gemini 3.1 Pro is still the flagship)
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.
Strong intelligence-per-dollar - Artificial Analysis Intelligence Index 56 at introductory $0.75/$3.75 pricing
Gemini 3.7 Flash
Fugu Ultra v2.0 is comparatively weak here — pricing rises to roughly $10/$45 per million tokens for prompts above 272K tokens
1M-token context with full multimodal input (text, image, audio, video)
Gemini 3.7 Flash
Google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed — and it runs cheaper at $0.75/$3.75 per 1M tokens.
Built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra
Gemini 3.7 Flash
Gemini 3.7 Flash lists built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra among its strengths; Fugu Ultra v2.0 does not.
Lowest cost at scale
Gemini 3.7 Flash
At $0.75/$3.75 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
→ Gemini 3.7 Flash
At $0.75/$3.75 per 1M tokens it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 3.7 Flash
Larger 1M window fits more in one prompt.
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
It is specifically built for that.
Anyone whose priority is strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing
→ Gemini 3.7 Flash
That is its strongest area.
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 are real: 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.
Gemini 3.7 Flash: where it fits
Google's cheap, fast coding-and-agents workhorse - AA Index 56, a 1M context, and aggressive introductory pricing that beats GPT-5.6 Terra on value and speed. Released August 13, 2026 by Google, it is built for strong intelligence-per-dollar - Artificial Analysis Intelligence Index 56 at introductory $0.75/$3.75 pricing, 1M-token context with full multimodal input (text, image, audio, video), built for coding and agents, with roughly 3x faster output than GPT-5.6 Terra, and wins broad-coding and web-development benchmarks against GPT-5.6 Terra.
Its trade-offs: introductory pricing ($0.75/$3.75) reverts to $1.50/$7.50 on Jan 1, 2027, trails GPT-5.6 Terra on the hardest repo-scale and terminal-agent coding, a fast 'workhorse,' not Google's top-intelligence model (Gemini 3.1 Pro is still the flagship), and some benchmark gains are Google's own figures. At $0.75 in / $3.75 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Fugu Ultra v2.0 and Gemini 3.7 Flash overlap enough that the right pick depends on your specific job. Gemini 3.7 Flash costs less per token; Gemini 3.7 Flash holds the larger context; and each leads in its own area — 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, Gemini 3.7 Flash for strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Fugu Ultra v2.0 and Gemini 3.7 Flash 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 Fugu Ultra v2.0 or Gemini 3.7 Flash 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, 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 while Gemini 3.7 Flash leans toward strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Ultra v2.0 or Gemini 3.7 Flash?
Gemini 3.7 Flash is cheaper — $5/$30 per 1M tokens vs $0.75/$3.75 per 1M tokens, roughly 6.7× apart on input.
Which has the bigger context window?
Effectively neither — 1M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Fugu Ultra v2.0 and Gemini 3.7 Flash together?
Yes — a multi-model platform like LumiChats gives you Fugu Ultra v2.0, Gemini 3.7 Flash 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, Fugu Ultra v2.0 or Gemini 3.7 Flash?
Fugu Ultra v2.0 — released September 10, 2026, about 28 days after Gemini 3.7 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.