Compare Gemini 3.1 Pro and GPT-5.6 Sol: Multimodal vs Frontier Reasoning
Gemini 3.1 Pro vs GPT-5.6 Sol: which should I use?
Gemini 3.1 Pro leads in context window (2M tokens vs 1M) and native audio/video modalities, while GPT-5.6 Sol excels in autonomous multi-step software engineering and complex agentic logic. Verified 2026-09-07.
Verified 2026-09-07
Where can you find price, speed, and task evidence for Gemini 3.1 Pro and GPT-5.6 Sol?
Which tasks fit Gemini 3.1 Pro and GPT-5.6 Sol?
Best-fit task signals from the published model strengths; this is not a substitute for a controlled benchmark.
| Fact | Gemini 3.1 Pro | GPT-5.6 Sol |
|---|---|---|
| Best fit | Whole-codebase, whole-document, or long-video analysis in a single request. | Complex, multi-step professional and coding work where accuracy matters more than cost. |
| Reasoning mode | Available | Available |
What does a Coding Agent workload cost with Gemini 3.1 Pro and GPT-5.6 Sol?
Modeled for Coding Agent: 20,000 input + 2,000 output tokens per task, 1 turn. This is a workload model, not a provider quote.
| Fact | Gemini 3.1 Pro | GPT-5.6 Sol |
|---|---|---|
| Coding Agent / task | $0.06 (modeled) (winner) | $0.12 (modeled) |
| Input / output rate | $2.00 / $12.00 per M | $4.00 / $20.00 per M |
How fast are Gemini 3.1 Pro and GPT-5.6 Sol?
Only non-estimated benchmark results are shown as measured.
| Fact | Gemini 3.1 Pro | GPT-5.6 Sol |
|---|---|---|
| Measured throughput | 55 tokens/s (winner) | 44 tokens/s |
| Time to first token | 420 ms | 560 ms |
How compatible are Gemini 3.1 Pro and GPT-5.6 Sol with APIs?
Provider-level wire-format and SDK facts; model-specific parameter differences may still apply.
| Fact | Gemini 3.1 Pro | GPT-5.6 Sol |
|---|---|---|
| OpenAI SDK | Not drop-in | Usable |
| Request shape | contents/parts structure instead of messages; an OpenAI-compatible endpoint exists but only covers a subset of parameters. | Canonical /chat/completions and /responses shape — every OpenAI-compatible provider on this site imitates it. |
| Streaming | SSE (Gemini streamGenerateContent) | SSE (OpenAI delta) |
What are the privacy and retention policies for Gemini 3.1 Pro and GPT-5.6 Sol?
Provider policy and residency facts from the verified provider registry. A missing retention policy is not treated as a guarantee.
| Fact | Gemini 3.1 Pro | GPT-5.6 Sol |
|---|---|---|
| Provider says API data trains models | No | No |
| Published retention period | Unavailable | Unavailable |
| Data residency | Global by default; Vertex AI offers selectable regional endpoints | US by default; EU data residency available on enterprise agreements |
How much effort does it take to migrate between Gemini 3.1 Pro and GPT-5.6 Sol?
Direction is from each displayed model to the other. Effort is derived from provider compatibility and published parameter maps.
| Fact | Gemini 3.1 Pro | GPT-5.6 Sol |
|---|---|---|
| Move Gemini 3.1 Pro → GPT-5.6 Sol | config; 2 breaking parameter differences | Target: GPT-5.6 Sol |
| Move GPT-5.6 Sol → Gemini 3.1 Pro | Source: GPT-5.6 Sol | code-change; 1 breaking parameter difference |
| Why | Keep the `openai` SDK; change `baseURL` and the API key. | contents/parts structure instead of messages; an OpenAI-compatible endpoint exists but only covers a subset of parameters. |
Batch 63 · exact-pair decision contributions · verified 2026-09-07
Exact pair boundary: Google / OpenAI; model endpoint, 2M vs 1M context scale, audio/video vs text/image modalities, and reasoning costs must join. Requested models are gemini-3.1-pro and gpt-5.6-sol. Provider, rate, pricing, and task pages remain fact owners.
Context window scale (2M vs 1M) and modality admissibility gate
Frozen Batch 63 scenario board. Formula / deterministic rule: admissible = (audio_or_video ? Gemini : Both) && (context <= 1M ? Both : (context <= 2M ? Gemini : Excluded)) Boundary: Owns context scaling and modality gating between Gemini 3.1 Pro and GPT-5.6 Sol.
| Frozen scenario / field ID | Pair, identity, host, surface, and evidence fields | Result | State |
|---|---|---|---|
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m1-r1text & image prompt (500K context) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=text & image prompt (500K context); task type; input context; video/audio required; Gemini eligible; Sol eligible; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — text & image prompt (500K context) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m1-r2video analysis prompt (100K context) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=video analysis prompt (100K context); task type; input context; video/audio required; Gemini eligible; Sol eligible; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — video analysis prompt (100K context) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m1-r3extreme text prompt (1.5M context) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=extreme text prompt (1.5M context); task type; input context; video/audio required; Gemini eligible; Sol eligible; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — extreme text prompt (1.5M context) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m1-r4multimodal audio call (250K context) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=multimodal audio call (250K context); task type; input context; video/audio required; Gemini eligible; Sol eligible; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — multimodal audio call (250K context) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m1-r52M max context boundary test | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=2M max context boundary test; task type; input context; video/audio required; Gemini eligible; Sol eligible; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 2M max context boundary test is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m1-r6unsupported modality request | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=unsupported modality request; task type; input context; video/audio required; Gemini eligible; Sol eligible; routing verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — unsupported modality request has no matched, dated bilateral observation. | FAIL CLOSED — manual, probe, or source evidence required |
First-party provenance: Google Gemini API model documentation; verification date 2026-09-07. Missing or conflicting joins fail closed.
Promotional versus standard token billing crossover
Frozen Batch 63 scenario board. Formula / deterministic rule: cost_delta = sol_monthly_bill - gemini_monthly_bill; Sol promo ends 2026-11-21 Boundary: Owns pricing differential modeling taking into account OpenAI promotional schedules.
| Frozen scenario / field ID | Pair, identity, host, surface, and evidence fields | Result | State |
|---|---|---|---|
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m2-r110K queries under Sol promo rate ($4/$20) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=10K queries under Sol promo rate ($4/$20); query volume; Gemini spend; Sol promo spend; Sol standard spend; post-promo budget increase; cost verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 10K queries under Sol promo rate ($4/$20) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m2-r250K queries under Sol standard rate ($5/$30) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=50K queries under Sol standard rate ($5/$30); query volume; Gemini spend; Sol promo spend; Sol standard spend; post-promo budget increase; cost verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 50K queries under Sol standard rate ($5/$30) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m2-r3100K high-volume document queries | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=100K high-volume document queries; query volume; Gemini spend; Sol promo spend; Sol standard spend; post-promo budget increase; cost verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — 100K high-volume document queries is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m2-r4prompt caching active (50% both) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=prompt caching active (50% both); query volume; Gemini spend; Sol promo spend; Sol standard spend; post-promo budget increase; cost verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — prompt caching active (50% both) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m2-r5batch queue active (50% both) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=batch queue active (50% both); query volume; Gemini spend; Sol promo spend; Sol standard spend; post-promo budget increase; cost verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — batch queue active (50% both) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m2-r6unresolved billing tariff schedule | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=unresolved billing tariff schedule; query volume; Gemini spend; Sol promo spend; Sol standard spend; post-promo budget increase; cost verdict; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — unresolved billing tariff schedule has no matched, dated bilateral observation. | FAIL CLOSED — manual, probe, or source evidence required |
First-party provenance: OpenAI API pricing; verification date 2026-09-07. Missing or conflicting joins fail closed.
Dual-routing canary and enterprise defect error budget
Frozen Batch 63 scenario board. Formula / deterministic rule: break_even_accuracy = (sol_cost / gemini_cost) - 1; defect loss saved justifies Sol spend Boundary: Owns accuracy-versus-cost trade-off modeling without speculative assertions.
| Frozen scenario / field ID | Pair, identity, host, surface, and evidence fields | Result | State |
|---|---|---|---|
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m3-r1zero defect cost (raw cost comparison) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=zero defect cost (raw cost comparison); scenario; Gemini monthly spend; Sol monthly spend; cost delta; required accuracy uplift; financial recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — zero defect cost (raw cost comparison) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m3-r2low defect penalty ($10 per error) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=low defect penalty ($10 per error); scenario; Gemini monthly spend; Sol monthly spend; cost delta; required accuracy uplift; financial recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — low defect penalty ($10 per error) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m3-r3medium defect penalty ($50 per error) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=medium defect penalty ($50 per error); scenario; Gemini monthly spend; Sol monthly spend; cost delta; required accuracy uplift; financial recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — medium defect penalty ($50 per error) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m3-r4high-stakes defect penalty ($200 per error) | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=high-stakes defect penalty ($200 per error); scenario; Gemini monthly spend; Sol monthly spend; cost delta; required accuracy uplift; financial recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — high-stakes defect penalty ($200 per error) is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m3-r5dual-routing 10% canary audit | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=dual-routing 10% canary audit; scenario; Gemini monthly spend; Sol monthly spend; cost delta; required accuracy uplift; financial recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — dual-routing 10% canary audit is a frozen fixture pending exact identity, configuration, and denominator joins. | UNTESTED — assumption cannot establish a verdict |
batch63-gemini-3-1-pro-vs-gpt-5-6-sol-m3-r6unresolved defect valuation | pair=gemini-3.1-pro vs gpt-5.6-sol; provider=Google / OpenAI; hostA=generativelanguage.googleapis.com; hostB=api.openai.com; surfaceA=Google AI Studio / Vertex AI; surfaceB=OpenAI Responses API; requested/effective IDs=gemini-3.1-pro,gpt-5.6-sol; scenario=unresolved defect valuation; scenario; Gemini monthly spend; Sol monthly spend; cost delta; required accuracy uplift; financial recommendation; prompt/config/input/output/result/cache/checkpoint/artifact hashes=required; evidence=2026-09-07; measurement versus assumption=explicit | Unavailable — unresolved defect valuation has no matched, dated bilateral observation. | FAIL CLOSED — manual, probe, or source evidence required |
First-party provenance: OpenAI model documentation; verification date 2026-09-07. Missing or conflicting joins fail closed.
Method and limitations: formulas are deterministic; observed and assumed inputs are labeled; no missing provider, host, account, region, realm, alias, snapshot, revision, weight, artifact, control, tool, modality, workload, rate-period, timestamp, or result is transferred. Run the gemini-3-1-pro-vs-gpt-5-6-sol Batch 63 scenario →
How do Gemini 3.1 Pro and GPT-5.6 Sol compare on specs?
| Gemini 3.1 Pro | GPT-5.6 Sol | |
|---|---|---|
| Price (input) | $2.00/M ✓ | $4.00/M |
| Price (output) | $12.00/M ✓ | $20.00/M |
| Blended price | $4.50/M ✓ | $8.00/M |
| Context window | 2,000,000 tokens ✓ | 1,000,000 tokens |
| Max output | 64,000 tokens | 128,000 tokens ✓ |
| Modalities | text, vision, audio | text, vision |
| Reasoning mode | Yes | Yes |
| Released | 2026-02 | 2026-06 |
| Speed | 55 t/s ✓ | 44 t/s |
How much do Gemini 3.1 Pro and GPT-5.6 Sol cost at scale?
| Tokens / month | Gemini 3.1 Pro | GPT-5.6 Sol | Delta |
|---|---|---|---|
| 1,000,000 | $4.50 | $8.00 | $3.50 (1.8×) |
| 10,000,000 | $45.00 | $80.00 | $35.00 (1.8×) |
| 100,000,000 | $450.00 | $800.00 | $350.00 (1.8×) |
Choose Gemini 3.1 Pro if…
- ✓Largest context window of any current model (2M tokens)
- ✓Native audio and video understanding
- ✓Google Search grounding
- ✓Whole-codebase, whole-document, or long-video analysis in a single request.
Choose GPT-5.6 Sol if…
- ✓Strongest OpenAI model for agentic, long-horizon coding
- ✓Deep reasoning mode for multi-step planning
- ✓Native vision input and 1M context
- ✓Complex, multi-step professional and coding work where accuracy matters more than cost.
Run this exact matchup right now
Send the same prompt to Gemini 3.1 Pro and GPT-5.6 Sol side by side and see the outputs yourself.
Try Gemini 3.1 Pro vs GPT-5.6 Sol FreeWhat are common questions about Gemini 3.1 Pro and GPT-5.6 Sol?
Is Gemini 3.1 Pro cheaper than GPT-5.6 Sol?
Gemini 3.1 Pro is cheaper, at $4.50 per million blended tokens vs $8.00 for GPT-5.6 Sol.
Which has the bigger context window, Gemini 3.1 Pro or GPT-5.6 Sol?
Gemini 3.1 Pro has the larger context window: 2,000,000 tokens vs 1,000,000.
Can Gemini 3.1 Pro replace GPT-5.6 Sol for coding?
Both are viable for coding. Largest context window of any current model (2M tokens) (Gemini 3.1 Pro) vs Strongest OpenAI model for agentic, long-horizon coding (GPT-5.6 Sol) — pick based on which strength matters more for your workload.
Which is faster, Gemini 3.1 Pro or GPT-5.6 Sol?
Gemini 3.1 Pro is faster: 55 t/s vs 44 t/s, measured on our speed benchmarks.
Neither of these? See Gemini 3.1 Pro alternatives or GPT-5.6 Sol alternatives.
What related comparisons help choose between Gemini 3.1 Pro and GPT-5.6 Sol?
Gemini 3.1 Pro pricingGPT-5.6 Sol pricingvs Claude Opus 4.8vs Claude Sonnet 5vs DeepSeek V4 Provs Grok 4.3Premium model tests
Pricing verified 2026-04-06. Specs verified 2026-08-14.