Pick Gemini 3.1 Pro for full multimodal input — text, image, audio and video in one 1m-token window or long video and document analysis. Pick GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation or fast, affordable execution while keeping respectable coding. On a tight budget at scale, GPT-5.6 Luna is the value pick.
Gemini 3.1 Pro (Google) and GPT-5.6 Luna (OpenAI) are two of the models people most often weigh against each other in 2026. Gemini 3.1 Pro is a 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. GPT-5.6 Luna is the budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: GPT-5.6 Luna is about 2× cheaper on input ($1/$6 per 1M tokens vs $2/$12 per 1M tokens) — meaningful once you are processing millions of tokens a month.
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: GPT-5.6 Luna is the newer model by about 5 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemini 3.1 Pro
GPT-5.6 Luna
Provider
Google (US)
OpenAI (US)
Released
February 19, 2026
July 9, 2026
Context window
1M (~1,573 pages)
1M (~1,500 pages)
Price (in/out)
$2/$12 per 1M tokens
$1/$6 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
26.3%
Not published
Who wins what
Full multimodal input — text, image, audio and video in one 1M-token window: Gemini 3.1 Pro — GPT-5.6 Luna is comparatively weak here — weak long-context recall deep in its 1M window (MRCR far below Sol)
Long video and document analysis: Gemini 3.1 Pro — Gemini 3.1 Pro lists long video and document analysis among its strengths; GPT-5.6 Luna does not.
Agentic reasoning (high ARC-AGI-2): Gemini 3.1 Pro — Gemini 3.1 Pro lists agentic reasoning (high ARC-AGI-2) among its strengths; GPT-5.6 Luna does not.
Cheapest GPT-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — At $1/$6 per 1M tokens it undercuts Gemini 3.1 Pro ($2/$12 per 1M tokens), and that gap compounds at volume.
Fast, affordable execution while keeping respectable coding: GPT-5.6 Luna — The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning — and it runs cheaper at $1/$6 per 1M tokens.
Same 1M context and programmatic tool calling as its siblings: GPT-5.6 Luna — Gemini 3.1 Pro is comparatively weak here — long-context recall drops sharply past 256K (26.3% on MRCR v2 at 1M)
Lowest cost at scale: GPT-5.6 Luna — At $1/$6 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: GPT-5.6 Luna — At $1/$6 per 1M tokens it undercuts Gemini 3.1 Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemini 3.1 Pro — Larger 1M window fits more in one prompt.
Anyone whose priority is full multimodal input — text, image, audio and video in one 1m-token window: Gemini 3.1 Pro — It is specifically built for that.
Anyone whose priority is cheapest gpt-5.6 tier for high-volume drafting and automation: GPT-5.6 Luna — That is its strongest area.
Gemini 3.1 Pro: where it fits
A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. Released February 19, 2026 by Google, it is built for full multimodal input — text, image, audio and video in one 1M-token window, long video and document analysis, agentic reasoning (high ARC-AGI-2), and broad multimodal understanding across formats.
Its trade-offs are real: long-context recall drops sharply past 256K (26.3% on MRCR v2 at 1M), premium price per token at $2/$12, and superseded within Google's own line by the newer 3.5/3.6 Flash releases for cost-sensitive work. At $2 in / $12 out per million tokens, it sits in the mid price band.
GPT-5.6 Luna: where it fits
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Released July 9, 2026 by OpenAI, it is built for cheapest GPT-5.6 tier for high-volume drafting and automation, fast, affordable execution while keeping respectable coding, same 1M context and programmatic tool calling as its siblings, and high-throughput simple agentic jobs.
Its trade-offs: weak long-context recall deep in its 1M window (MRCR far below Sol), and lowest raw capability of the three GPT-5.6 tiers; no open weights. At $1 in / $6 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Gemini 3.1 Pro and GPT-5.6 Luna overlap enough that the right pick depends on your specific job. GPT-5.6 Luna costs less per token; Gemini 3.1 Pro holds the larger context; and each leads in its own area — Gemini 3.1 Pro for full multimodal input — text, image, audio and video in one 1m-token window, GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Gemini 3.1 Pro or GPT-5.6 Luna 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 3.1 Pro leans toward full multimodal input — text, image, audio and video in one 1m-token window while GPT-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.1 Pro or GPT-5.6 Luna?
GPT-5.6 Luna is cheaper — $2/$12 per 1M tokens vs $1/$6 per 1M tokens, roughly 2× 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 3.1 Pro and GPT-5.6 Luna together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Pro, GPT-5.6 Luna 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 3.1 Pro or GPT-5.6 Luna?
GPT-5.6 Luna — released July 9, 2026, about 5 months after Gemini 3.1 Pro.
Gemini 3.1 Pro vs GPT-5.6 Luna
Google · US | OpenAI · US · Updated June 2026
Quick verdict
Pick Gemini 3.1 Pro for full multimodal input — text, image, audio and video in one 1m-token window or long video and document analysis. Pick GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation or fast, affordable execution while keeping respectable coding. On a tight budget at scale, GPT-5.6 Luna is the value pick.
Gemini 3.1 Pro (Google) and GPT-5.6 Luna (OpenAI) are two of the models people most often weigh against each other in 2026. Gemini 3.1 Pro is a 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. GPT-5.6 Luna is the budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GPT-5.6 Luna is about 2× cheaper on input ($1/$6 per 1M tokens vs $2/$12 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸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: GPT-5.6 Luna is the newer model by about 5 months (released July 9, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemini 3.1 Pro
GPT-5.6 Luna
Provider
Google (US)
OpenAI (US)
Released
February 19, 2026
July 9, 2026
Context window
1M (~1,573 pages)
1M (~1,500 pages)
Price (in/out)
$2/$12 per 1M tokens
$1/$6 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
26.3%
Not published
Who wins what
Full multimodal input — text, image, audio and video in one 1M-token window
Gemini 3.1 Pro
GPT-5.6 Luna is comparatively weak here — weak long-context recall deep in its 1M window (MRCR far below Sol)
Long video and document analysis
Gemini 3.1 Pro
Gemini 3.1 Pro lists long video and document analysis among its strengths; GPT-5.6 Luna does not.
Agentic reasoning (high ARC-AGI-2)
Gemini 3.1 Pro
Gemini 3.1 Pro lists agentic reasoning (high ARC-AGI-2) among its strengths; GPT-5.6 Luna does not.
Cheapest GPT-5.6 tier for high-volume drafting and automation
GPT-5.6 Luna
At $1/$6 per 1M tokens it undercuts Gemini 3.1 Pro ($2/$12 per 1M tokens), and that gap compounds at volume.
Fast, affordable execution while keeping respectable coding
GPT-5.6 Luna
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning — and it runs cheaper at $1/$6 per 1M tokens.
Same 1M context and programmatic tool calling as its siblings
GPT-5.6 Luna
Gemini 3.1 Pro is comparatively weak here — long-context recall drops sharply past 256K (26.3% on MRCR v2 at 1M)
Lowest cost at scale
GPT-5.6 Luna
At $1/$6 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
→ GPT-5.6 Luna
At $1/$6 per 1M tokens it undercuts Gemini 3.1 Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 3.1 Pro
Larger 1M window fits more in one prompt.
Anyone whose priority is full multimodal input — text, image, audio and video in one 1m-token window
→ Gemini 3.1 Pro
It is specifically built for that.
Anyone whose priority is cheapest gpt-5.6 tier for high-volume drafting and automation
→ GPT-5.6 Luna
That is its strongest area.
Gemini 3.1 Pro: where it fits
A 1M-token multimodal workhorse — huge breadth across text, image, audio and video, but recall fades deep in the window. Released February 19, 2026 by Google, it is built for full multimodal input — text, image, audio and video in one 1M-token window, long video and document analysis, agentic reasoning (high ARC-AGI-2), and broad multimodal understanding across formats.
Its trade-offs are real: long-context recall drops sharply past 256K (26.3% on MRCR v2 at 1M), premium price per token at $2/$12, and superseded within Google's own line by the newer 3.5/3.6 Flash releases for cost-sensitive work. At $2 in / $12 out per million tokens, it sits in the mid price band.
GPT-5.6 Luna: where it fits
The budget, high-throughput GPT-5.6 tier — built for cheap, fast, large-volume work rather than deep long-context reasoning. Released July 9, 2026 by OpenAI, it is built for cheapest GPT-5.6 tier for high-volume drafting and automation, fast, affordable execution while keeping respectable coding, same 1M context and programmatic tool calling as its siblings, and high-throughput simple agentic jobs.
Its trade-offs: weak long-context recall deep in its 1M window (MRCR far below Sol), and lowest raw capability of the three GPT-5.6 tiers; no open weights. At $1 in / $6 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Gemini 3.1 Pro and GPT-5.6 Luna overlap enough that the right pick depends on your specific job. GPT-5.6 Luna costs less per token; Gemini 3.1 Pro holds the larger context; and each leads in its own area — Gemini 3.1 Pro for full multimodal input — text, image, audio and video in one 1m-token window, GPT-5.6 Luna for cheapest gpt-5.6 tier for high-volume drafting and automation. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Gemini 3.1 Pro and GPT-5.6 Luna 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 3.1 Pro or GPT-5.6 Luna 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 3.1 Pro leans toward full multimodal input — text, image, audio and video in one 1m-token window while GPT-5.6 Luna leans toward cheapest gpt-5.6 tier for high-volume drafting and automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.1 Pro or GPT-5.6 Luna?
GPT-5.6 Luna is cheaper — $2/$12 per 1M tokens vs $1/$6 per 1M tokens, roughly 2× 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 3.1 Pro and GPT-5.6 Luna together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Pro, GPT-5.6 Luna 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 3.1 Pro or GPT-5.6 Luna?
GPT-5.6 Luna — released July 9, 2026, about 5 months after Gemini 3.1 Pro.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.