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). Pick GPT-5.5 for terminal, cli and computer-use automation or long-horizon tool sequencing. On a tight budget at scale, Gemini 3.7 Flash is the value pick.
Gemini 3.7 Flash (Google) and GPT-5.5 (OpenAI) are two of the models people most often weigh against each other in 2026. 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. GPT-5.5 is openAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. 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 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: Gemini 3.7 Flash is the newer model by about 4 months (released August 13, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemini 3.7 Flash
GPT-5.5
Provider
Google (US)
OpenAI (US)
Released
August 13, 2026
April 23, 2026
Context window
1M (~1,573 pages)
1M (~1,500 pages)
Price (in/out)
$0.75/$3.75 per 1M tokens
$5/$30 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, audio, video, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong intelligence-per-dollar - Artificial Analysis Intelligence Index 56 at introductory $0.75/$3.75 pricing: Gemini 3.7 Flash — GPT-5.5 is comparatively weak here — tiered long-context pricing 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 — GPT-5.5 is comparatively weak here — trails Opus 4.8 on hardest coding benchmarks
Terminal, CLI and computer-use automation: GPT-5.5 — Gemini 3.7 Flash is comparatively weak here — trails GPT-5.6 Terra on the hardest repo-scale and terminal-agent coding
Long-horizon tool sequencing: GPT-5.5 — GPT-5.5 lists long-horizon tool sequencing among its strengths; Gemini 3.7 Flash does not.
Strong agentic coding and reasoning: GPT-5.5 — GPT-5.5 lists strong agentic coding and reasoning among its strengths; Gemini 3.7 Flash 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 GPT-5.5, 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 strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing: Gemini 3.7 Flash — It is specifically built for that.
Anyone whose priority is terminal, cli and computer-use automation: GPT-5.5 — That is its strongest area.
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 are real: 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.
GPT-5.5: where it fits
OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. Released April 23, 2026 by OpenAI, it is built for terminal, CLI and computer-use automation, long-horizon tool sequencing, strong agentic coding and reasoning, and browser-driving agents.
Its trade-offs: trails Opus 4.8 on hardest coding benchmarks, and tiered long-context pricing above 272K tokens. At $5 in / $30 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
Gemini 3.7 Flash and GPT-5.5 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 — Gemini 3.7 Flash for strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing, GPT-5.5 for terminal, cli and computer-use automation. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Gemini 3.7 Flash or GPT-5.5 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 3.7 Flash leans toward strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing while GPT-5.5 leans toward terminal, cli and computer-use automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.7 Flash or GPT-5.5?
Gemini 3.7 Flash is cheaper — $0.75/$3.75 per 1M tokens vs $5/$30 per 1M tokens, roughly 6.7× apart on input.
Which has the bigger context window?
Effectively neither — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemini 3.7 Flash and GPT-5.5 together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.7 Flash, GPT-5.5 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 3.7 Flash or GPT-5.5?
Gemini 3.7 Flash — released August 13, 2026, about 4 months after GPT-5.5.
Gemini 3.7 Flash vs GPT-5.5
Google · US | OpenAI · US · Updated June 2026
Quick verdict
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). Pick GPT-5.5 for terminal, cli and computer-use automation or long-horizon tool sequencing. On a tight budget at scale, Gemini 3.7 Flash is the value pick.
Gemini 3.7 Flash (Google) and GPT-5.5 (OpenAI) are two of the models people most often weigh against each other in 2026. 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. GPT-5.5 is openAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. 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 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: Gemini 3.7 Flash is the newer model by about 4 months (released August 13, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemini 3.7 Flash
GPT-5.5
Provider
Google (US)
OpenAI (US)
Released
August 13, 2026
April 23, 2026
Context window
1M (~1,573 pages)
1M (~1,500 pages)
Price (in/out)
$0.75/$3.75 per 1M tokens
$5/$30 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, audio, video, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Strong intelligence-per-dollar - Artificial Analysis Intelligence Index 56 at introductory $0.75/$3.75 pricing
Gemini 3.7 Flash
GPT-5.5 is comparatively weak here — tiered long-context pricing 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
GPT-5.5 is comparatively weak here — trails Opus 4.8 on hardest coding benchmarks
Terminal, CLI and computer-use automation
GPT-5.5
Gemini 3.7 Flash is comparatively weak here — trails GPT-5.6 Terra on the hardest repo-scale and terminal-agent coding
Long-horizon tool sequencing
GPT-5.5
GPT-5.5 lists long-horizon tool sequencing among its strengths; Gemini 3.7 Flash does not.
Strong agentic coding and reasoning
GPT-5.5
GPT-5.5 lists strong agentic coding and reasoning among its strengths; Gemini 3.7 Flash 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 GPT-5.5, 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 strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing
→ Gemini 3.7 Flash
It is specifically built for that.
Anyone whose priority is terminal, cli and computer-use automation
→ GPT-5.5
That is its strongest area.
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 are real: 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.
GPT-5.5: where it fits
OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. Released April 23, 2026 by OpenAI, it is built for terminal, CLI and computer-use automation, long-horizon tool sequencing, strong agentic coding and reasoning, and browser-driving agents.
Its trade-offs: trails Opus 4.8 on hardest coding benchmarks, and tiered long-context pricing above 272K tokens. At $5 in / $30 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
Gemini 3.7 Flash and GPT-5.5 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 — Gemini 3.7 Flash for strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing, GPT-5.5 for terminal, cli and computer-use automation. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Gemini 3.7 Flash and GPT-5.5 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, Gemini 3.7 Flash leans toward strong intelligence-per-dollar - artificial analysis intelligence index 56 at introductory $0.75/$3.75 pricing while GPT-5.5 leans toward terminal, cli and computer-use automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.7 Flash or GPT-5.5?
Gemini 3.7 Flash is cheaper — $0.75/$3.75 per 1M tokens vs $5/$30 per 1M tokens, roughly 6.7× apart on input.
Which has the bigger context window?
Effectively neither — 1M vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Gemini 3.7 Flash and GPT-5.5 together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.7 Flash, GPT-5.5 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 3.7 Flash or GPT-5.5?
Gemini 3.7 Flash — released August 13, 2026, about 4 months after GPT-5.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.