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 3.5 Flash-Lite for the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work or simple classification, extraction and routing where flagship reasoning is wasted spend. On a tight budget at scale, Gemini 3.5 Flash-Lite is the value pick.
Fugu Ultra v2.0 (Sakana AI) and Gemini 3.5 Flash-Lite (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 3.5 Flash-Lite is google's cheapest July 2026 model at $0.30/$2.50 — a high-volume, low-cost Lite tier for simple work, not frontier reasoning. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Price: Gemini 3.5 Flash-Lite is about 17× cheaper on input ($0.3/$2.5 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 tokens (~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 51 days (released September 10, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Fugu Ultra v2.0
Gemini 3.5 Flash-Lite
Provider
Sakana AI (Global)
Google (US)
Released
September 10, 2026
July 21, 2026
Context window
1M tokens (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$5/$30 per 1M tokens
$0.3/$2.5 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text
text, image, 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 3.5 Flash-Lite is comparatively weak here — a Lite model — the weakest of the July 2026 Gemini line on hard reasoning and 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 — 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.
1M-token context window: Fugu Ultra v2.0 — Gemini 3.5 Flash-Lite is comparatively weak here — google did not publish its exact context window, so 1M is inferred from the family
The cheapest Gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work: Gemini 3.5 Flash-Lite — At $0.3/$2.5 per 1M tokens it undercuts Fugu Ultra v2.0 ($5/$30 per 1M tokens), and that gap compounds at volume.
Simple classification, extraction and routing where flagship reasoning is wasted spend: Gemini 3.5 Flash-Lite — Google's cheapest July 2026 model at $0.30/$2.50 — a high-volume, low-cost Lite tier for simple work, not frontier reasoning — and it runs cheaper at $0.3/$2.5 per 1M tokens.
Latency-sensitive pipelines that call a model on every request: Gemini 3.5 Flash-Lite — 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
Lowest cost at scale: Gemini 3.5 Flash-Lite — At $0.3/$2.5 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 3.5 Flash-Lite — At $0.3/$2.5 per 1M tokens it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.
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 the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work: Gemini 3.5 Flash-Lite — 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 3.5 Flash-Lite: where it fits
Google's cheapest July 2026 model at $0.30/$2.50 — a high-volume, low-cost Lite tier for simple work, not frontier reasoning. Released July 21, 2026 by Google, it is built for the cheapest Gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work, simple classification, extraction and routing where flagship reasoning is wasted spend, latency-sensitive pipelines that call a model on every request, and pairing with a stronger model as the cheap first pass in a cascade.
Its trade-offs: a Lite model — the weakest of the July 2026 Gemini line on hard reasoning and coding, google did not publish its exact context window, so 1M is inferred from the family, no published SWE-Bench Verified score, and outclassed by 3.6 Flash whenever a task needs real capability rather than raw throughput. At $0.3 in / $2.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Fugu Ultra v2.0 and Gemini 3.5 Flash-Lite overlap enough that the right pick depends on your specific job. Gemini 3.5 Flash-Lite costs less per token; 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 3.5 Flash-Lite for the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work. 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 3.5 Flash-Lite 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 3.5 Flash-Lite leans toward the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Ultra v2.0 or Gemini 3.5 Flash-Lite?
Gemini 3.5 Flash-Lite is cheaper — $5/$30 per 1M tokens vs $0.3/$2.5 per 1M tokens, roughly 17× apart on input.
Which has the bigger context window?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Fugu Ultra v2.0 and Gemini 3.5 Flash-Lite together?
Yes — a multi-model platform like LumiChats gives you Fugu Ultra v2.0, Gemini 3.5 Flash-Lite 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 3.5 Flash-Lite?
Fugu Ultra v2.0 — released September 10, 2026, about 51 days after Gemini 3.5 Flash-Lite.
Fugu Ultra v2.0 vs Gemini 3.5 Flash-Lite
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 3.5 Flash-Lite for the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work or simple classification, extraction and routing where flagship reasoning is wasted spend. On a tight budget at scale, Gemini 3.5 Flash-Lite is the value pick.
Fugu Ultra v2.0 (Sakana AI) and Gemini 3.5 Flash-Lite (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 3.5 Flash-Lite is google's cheapest July 2026 model at $0.30/$2.50 — a high-volume, low-cost Lite tier for simple work, not frontier reasoning. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Price: Gemini 3.5 Flash-Lite is about 17× cheaper on input ($0.3/$2.5 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 tokens (~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 51 days (released September 10, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Fugu Ultra v2.0
Gemini 3.5 Flash-Lite
Provider
Sakana AI (Global)
Google (US)
Released
September 10, 2026
July 21, 2026
Context window
1M tokens (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$5/$30 per 1M tokens
$0.3/$2.5 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text
text, image, 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 3.5 Flash-Lite is comparatively weak here — a Lite model — the weakest of the July 2026 Gemini line on hard reasoning and 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
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.
1M-token context window
Fugu Ultra v2.0
Gemini 3.5 Flash-Lite is comparatively weak here — google did not publish its exact context window, so 1M is inferred from the family
The cheapest Gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work
Gemini 3.5 Flash-Lite
At $0.3/$2.5 per 1M tokens it undercuts Fugu Ultra v2.0 ($5/$30 per 1M tokens), and that gap compounds at volume.
Simple classification, extraction and routing where flagship reasoning is wasted spend
Gemini 3.5 Flash-Lite
Google's cheapest July 2026 model at $0.30/$2.50 — a high-volume, low-cost Lite tier for simple work, not frontier reasoning — and it runs cheaper at $0.3/$2.5 per 1M tokens.
Latency-sensitive pipelines that call a model on every request
Gemini 3.5 Flash-Lite
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
Lowest cost at scale
Gemini 3.5 Flash-Lite
At $0.3/$2.5 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 3.5 Flash-Lite
At $0.3/$2.5 per 1M tokens it undercuts Fugu Ultra v2.0, and on millions of tokens that margin decides the monthly bill.
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 the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work
→ Gemini 3.5 Flash-Lite
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 3.5 Flash-Lite: where it fits
Google's cheapest July 2026 model at $0.30/$2.50 — a high-volume, low-cost Lite tier for simple work, not frontier reasoning. Released July 21, 2026 by Google, it is built for the cheapest Gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work, simple classification, extraction and routing where flagship reasoning is wasted spend, latency-sensitive pipelines that call a model on every request, and pairing with a stronger model as the cheap first pass in a cascade.
Its trade-offs: a Lite model — the weakest of the July 2026 Gemini line on hard reasoning and coding, google did not publish its exact context window, so 1M is inferred from the family, no published SWE-Bench Verified score, and outclassed by 3.6 Flash whenever a task needs real capability rather than raw throughput. At $0.3 in / $2.5 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Fugu Ultra v2.0 and Gemini 3.5 Flash-Lite overlap enough that the right pick depends on your specific job. Gemini 3.5 Flash-Lite costs less per token; 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 3.5 Flash-Lite for the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work. 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 3.5 Flash-Lite 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 3.5 Flash-Lite 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 3.5 Flash-Lite leans toward the cheapest gemini tier at $0.30/$2.50 — built for the highest-volume, lowest-margin work, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Fugu Ultra v2.0 or Gemini 3.5 Flash-Lite?
Gemini 3.5 Flash-Lite is cheaper — $5/$30 per 1M tokens vs $0.3/$2.5 per 1M tokens, roughly 17× apart on input.
Which has the bigger context window?
Both advertise 1M tokens (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Fugu Ultra v2.0 and Gemini 3.5 Flash-Lite together?
Yes — a multi-model platform like LumiChats gives you Fugu Ultra v2.0, Gemini 3.5 Flash-Lite 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 3.5 Flash-Lite?
Fugu Ultra v2.0 — released September 10, 2026, about 51 days after Gemini 3.5 Flash-Lite.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.