Pick Gemini 3.8 Flash for long-horizon agentic coding (deepswe v1.1) or cost-efficient workhorse performance beating larger models at same price as 3.7 flash. Pick GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work or classification, extraction, ranking and sub-agent execution at scale. On a tight budget at scale, GPT-5.4 Nano is the value pick.
Gemini 3.8 Flash (Google DeepMind) and GPT-5.4 Nano (OpenAI) are two of the models people most often weigh against each other in 2026. Gemini 3.8 Flash is google's cost-efficient workhorse model released September 2, 2026, tuned for long-horizon coding and autonomous agents, launched alongside a restricted 'Cyber' variant for vulnerability research. GPT-5.4 Nano is openAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: GPT-5.4 Nano is about 3.8× cheaper on input ($0.2/$1.25 per 1M tokens vs $0.75/$3.75 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Gemini 3.8 Flash holds 2.5× more — 1M tokens (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Gemini 3.8 Flash is the newer model by about 6 months (released September 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemini 3.8 Flash
GPT-5.4 Nano
Provider
Google DeepMind (US)
OpenAI (US)
Released
September 2, 2026
March 17, 2026
Context window
1M tokens (~1,500 pages)
400K (~600 pages)
Price (in/out)
$0.75/$3.75 per 1M tokens
$0.2/$1.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, audio, video
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-horizon agentic coding (DeepSWE v1.1): Gemini 3.8 Flash — Its 1M tokens window holds about 2.5× more than GPT-5.4 Nano's 400K in a single prompt.
Cost-efficient workhorse performance beating larger models at same price as 3.7 Flash: Gemini 3.8 Flash — Google's cost-efficient workhorse model released September 2, 2026, tuned for long-horizon coding and autonomous agents, launched alongside a restricted 'Cyber' variant for vulnerability research — and it carries the larger 1M tokens context.
Vals Finance Agent V2 benchmark (61.4%, ahead of Claude Opus 5's 58.6%); also leads a weak field on the Harvey legal benchmark (10.0%): Gemini 3.8 Flash — Google's cost-efficient workhorse model released September 2, 2026, tuned for long-horizon coding and autonomous agents, launched alongside a restricted 'Cyber' variant for vulnerability research — and it is the newer of the two.
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens it undercuts Gemini 3.8 Flash ($0.75/$3.75 per 1M tokens), and that gap compounds at volume.
Classification, extraction, ranking and sub-agent execution at scale: GPT-5.4 Nano — OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning — and it runs cheaper at $0.2/$1.25 per 1M tokens.
A 400K context in the smallest, fastest GPT-5.4 variant: GPT-5.4 Nano — GPT-5.4 Nano lists a 400K context in the smallest, fastest GPT-5.4 variant among its strengths; Gemini 3.8 Flash does not.
Lowest cost at scale: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Gemini 3.8 Flash — Its 1M tokens window is about 2.5× larger than GPT-5.4 Nano's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens it undercuts Gemini 3.8 Flash, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemini 3.8 Flash — Larger 1M tokens window fits more in one prompt.
Anyone whose priority is long-horizon agentic coding (deepswe v1.1): Gemini 3.8 Flash — It is specifically built for that.
Anyone whose priority is cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — That is its strongest area.
Gemini 3.8 Flash: where it fits
Google's cost-efficient workhorse model released September 2, 2026, tuned for long-horizon coding and autonomous agents, launched alongside a restricted 'Cyber' variant for vulnerability research. Released September 2, 2026 by Google DeepMind, it is built for long-horizon agentic coding (DeepSWE v1.1), cost-efficient workhorse performance beating larger models at same price as 3.7 Flash, vals Finance Agent V2 benchmark (61.4%, ahead of Claude Opus 5's 58.6%); also leads a weak field on the Harvey legal benchmark (10.0%), and prompt-injection robustness (Gray Swan benchmark).
Its trade-offs are real: still a mid-tier 'Flash' model, not Google's frontier flagship (which remains unreleased), introductory price doubles on January 1, 2027, hLE-Verified score (54.9%) trails top frontier reasoning models, and built on the same base model as Gemini 3.7 Flash (a post-training update, not a freshly pretrained model). At $0.75 in / $3.75 out per million tokens, it sits in the budget price band.
GPT-5.4 Nano: where it fits
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Released March 17, 2026 by OpenAI, it is built for cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, classification, extraction, ranking and sub-agent execution at scale, a 400K context in the smallest, fastest GPT-5.4 variant, and text and image input for cheap multimodal pipelines.
Its trade-offs: a nano tier — not built for hard reasoning or frontier coding, no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead), outclassed by GPT-5.4 and GPT-5.4 Mini whenever a task needs real depth, and image input only — no audio or video. At $0.2 in / $1.25 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Gemini 3.8 Flash and GPT-5.4 Nano overlap enough that the right pick depends on your specific job. GPT-5.4 Nano costs less per token; Gemini 3.8 Flash holds the larger context; and each leads in its own area — Gemini 3.8 Flash for long-horizon agentic coding (deepswe v1.1), GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Gemini 3.8 Flash or GPT-5.4 Nano 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, Gemini 3.8 Flash leans toward long-horizon agentic coding (deepswe v1.1) while GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.8 Flash or GPT-5.4 Nano?
GPT-5.4 Nano is cheaper — $0.75/$3.75 per 1M tokens vs $0.2/$1.25 per 1M tokens, roughly 3.8× apart on input.
Which has the bigger context window?
Gemini 3.8 Flash — 1M tokens vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 3.8 Flash and GPT-5.4 Nano together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.8 Flash, GPT-5.4 Nano 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, Gemini 3.8 Flash or GPT-5.4 Nano?
Gemini 3.8 Flash — released September 2, 2026, about 6 months after GPT-5.4 Nano.
Gemini 3.8 Flash vs GPT-5.4 Nano
Google DeepMind · US | OpenAI · US · Updated June 2026
Quick verdict
Pick Gemini 3.8 Flash for long-horizon agentic coding (deepswe v1.1) or cost-efficient workhorse performance beating larger models at same price as 3.7 flash. Pick GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work or classification, extraction, ranking and sub-agent execution at scale. On a tight budget at scale, GPT-5.4 Nano is the value pick.
Gemini 3.8 Flash (Google DeepMind) and GPT-5.4 Nano (OpenAI) are two of the models people most often weigh against each other in 2026. Gemini 3.8 Flash is google's cost-efficient workhorse model released September 2, 2026, tuned for long-horizon coding and autonomous agents, launched alongside a restricted 'Cyber' variant for vulnerability research. GPT-5.4 Nano is openAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GPT-5.4 Nano is about 3.8× cheaper on input ($0.2/$1.25 per 1M tokens vs $0.75/$3.75 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Gemini 3.8 Flash holds 2.5× more — 1M tokens (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Gemini 3.8 Flash is the newer model by about 6 months (released September 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemini 3.8 Flash
GPT-5.4 Nano
Provider
Google DeepMind (US)
OpenAI (US)
Released
September 2, 2026
March 17, 2026
Context window
1M tokens (~1,500 pages)
400K (~600 pages)
Price (in/out)
$0.75/$3.75 per 1M tokens
$0.2/$1.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, audio, video
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-horizon agentic coding (DeepSWE v1.1)
Gemini 3.8 Flash
Its 1M tokens window holds about 2.5× more than GPT-5.4 Nano's 400K in a single prompt.
Cost-efficient workhorse performance beating larger models at same price as 3.7 Flash
Gemini 3.8 Flash
Google's cost-efficient workhorse model released September 2, 2026, tuned for long-horizon coding and autonomous agents, launched alongside a restricted 'Cyber' variant for vulnerability research — and it carries the larger 1M tokens context.
Vals Finance Agent V2 benchmark (61.4%, ahead of Claude Opus 5's 58.6%); also leads a weak field on the Harvey legal benchmark (10.0%)
Gemini 3.8 Flash
Google's cost-efficient workhorse model released September 2, 2026, tuned for long-horizon coding and autonomous agents, launched alongside a restricted 'Cyber' variant for vulnerability research — and it is the newer of the two.
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens it undercuts Gemini 3.8 Flash ($0.75/$3.75 per 1M tokens), and that gap compounds at volume.
Classification, extraction, ranking and sub-agent execution at scale
GPT-5.4 Nano
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning — and it runs cheaper at $0.2/$1.25 per 1M tokens.
A 400K context in the smallest, fastest GPT-5.4 variant
GPT-5.4 Nano
GPT-5.4 Nano lists a 400K context in the smallest, fastest GPT-5.4 variant among its strengths; Gemini 3.8 Flash does not.
Lowest cost at scale
GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Gemini 3.8 Flash
Its 1M tokens window is about 2.5× larger than GPT-5.4 Nano's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens it undercuts Gemini 3.8 Flash, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 3.8 Flash
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is long-horizon agentic coding (deepswe v1.1)
→ Gemini 3.8 Flash
It is specifically built for that.
Anyone whose priority is cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
→ GPT-5.4 Nano
That is its strongest area.
Gemini 3.8 Flash: where it fits
Google's cost-efficient workhorse model released September 2, 2026, tuned for long-horizon coding and autonomous agents, launched alongside a restricted 'Cyber' variant for vulnerability research. Released September 2, 2026 by Google DeepMind, it is built for long-horizon agentic coding (DeepSWE v1.1), cost-efficient workhorse performance beating larger models at same price as 3.7 Flash, vals Finance Agent V2 benchmark (61.4%, ahead of Claude Opus 5's 58.6%); also leads a weak field on the Harvey legal benchmark (10.0%), and prompt-injection robustness (Gray Swan benchmark).
Its trade-offs are real: still a mid-tier 'Flash' model, not Google's frontier flagship (which remains unreleased), introductory price doubles on January 1, 2027, hLE-Verified score (54.9%) trails top frontier reasoning models, and built on the same base model as Gemini 3.7 Flash (a post-training update, not a freshly pretrained model). At $0.75 in / $3.75 out per million tokens, it sits in the budget price band.
GPT-5.4 Nano: where it fits
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Released March 17, 2026 by OpenAI, it is built for cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, classification, extraction, ranking and sub-agent execution at scale, a 400K context in the smallest, fastest GPT-5.4 variant, and text and image input for cheap multimodal pipelines.
Its trade-offs: a nano tier — not built for hard reasoning or frontier coding, no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead), outclassed by GPT-5.4 and GPT-5.4 Mini whenever a task needs real depth, and image input only — no audio or video. At $0.2 in / $1.25 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Gemini 3.8 Flash and GPT-5.4 Nano overlap enough that the right pick depends on your specific job. GPT-5.4 Nano costs less per token; Gemini 3.8 Flash holds the larger context; and each leads in its own area — Gemini 3.8 Flash for long-horizon agentic coding (deepswe v1.1), GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Gemini 3.8 Flash and GPT-5.4 Nano 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 Gemini 3.8 Flash or GPT-5.4 Nano 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, Gemini 3.8 Flash leans toward long-horizon agentic coding (deepswe v1.1) while GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.8 Flash or GPT-5.4 Nano?
GPT-5.4 Nano is cheaper — $0.75/$3.75 per 1M tokens vs $0.2/$1.25 per 1M tokens, roughly 3.8× apart on input.
Which has the bigger context window?
Gemini 3.8 Flash — 1M tokens vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 3.8 Flash and GPT-5.4 Nano together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.8 Flash, GPT-5.4 Nano 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, Gemini 3.8 Flash or GPT-5.4 Nano?
Gemini 3.8 Flash — released September 2, 2026, about 6 months after GPT-5.4 Nano.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.