Google has 5 models in The AI Leaderboard directory: Gemini 3.7 Flash, Gemini 3.1 Pro, Gemini 3 Pro, Gemini 3 Deep Think, Gemma 4. This provider hub compares their verified availability, licensing, context windows, pricing references and intended uses, with direct links to every model guide.
Quick answer: Gemini 3.7 Flash is Google's highest-ranked model here at #7 with an Overall score of 78.8. Use the lineup table below to compare it with the provider’s other current, specialist, open-weight or migration-reference models.
Google model lineup at a glance
Metric | Current directory value |
|---|---|
Models covered | 5 |
Currently ranked | 1 |
Open-weight models | 1 |
Restricted models | 0 |
Legacy or migration references | 1 |
Highest-ranked model | Gemini 3.7 Flash, #7, Overall 78.8 |
Last verified | September 2, 2026 |
Complete Google model directory
Model names in this table link directly to their complete guides. Status and pricing can change, so confirm the active endpoint and provider terms before procurement or migration.
Model | Status | License | Context | Best fit |
|---|---|---|---|---|
Available | Proprietary | 1,048,576 tokens | Fast multimodal agents and high-volume applications | |
Available to Google AI Ultra subscribers | Proprietary | 1 million tokens | difficult science, mathematics, research and engineering reasoning | |
Available in selected products; API preview retired in favor of 3.1 Pro | Proprietary | 1,048,576 tokens | historical multimodal reasoning comparisons and migration testing | |
Preview | Proprietary | 1,048,576 tokens | multimodal reasoning, complex problem solving, software engineering and large mixed-media inputs | |
Available; downloadable model family | Open weights under the Gemma license | Up to 256,000 tokens depending on variant | open multimodal agents, on-device work and size-flexible deployment |
How the Google models differ
Model | Directory role | Modalities | Maximum output | Access |
|---|---|---|---|---|
Gemini 3.7 Flash | Available proprietary | Text, image, video, audio and PDF input; text output | 65,536 tokens | See the guide for current access routes |
Gemini 3 Deep Think | Available proprietary | Multimodal input; text output through the Gemini app | Product-managed; no standalone public API maximum | Gemini app for Google AI Ultra subscribers and selected research programs |
Gemini 3 Pro | Legacy or migration | Text, image, video, audio and PDF input; text output | 65,536 tokens | Gemini products and legacy/partner surfaces; new API work should use Gemini 3.1 Pro |
Gemini 3.1 Pro | Preview | Text, image, video, audio and PDF input; text output | 65,536 tokens | Gemini API, AI Studio, Vertex AI, Gemini Enterprise, Gemini app, NotebookLM, Gemini CLI and Android Studio |
Gemma 4 | Open weights | Text and image input; selected variants support audio; text output | Variant-specific within the context budget | Google AI tooling, Hugging Face and compatible local or cloud runtimes |
The labels above describe access and lifecycle, not a hidden capability ranking. Only 1 Google model in the current top eight receive a rank on this site. Other guides remain unranked until comparable evidence is available.
Google model pricing
Model | Pricing reference | Cost caveat |
|---|---|---|
Gemini 3.7 Flash | $0.75 input / $3.75 output per million tokens, introductory | Caching, tools, long context and regional rates may differ |
Gemini 3 Deep Think | Included with eligible Google AI Ultra access; no standalone token price | Caching, tools, long context and regional rates may differ |
Gemini 3 Pro | Historical API pricing was tiered; use Gemini 3.1 Pro pricing for new integrations | Caching, tools, long context and regional rates may differ |
Gemini 3.1 Pro | Tiered Gemini API pricing varies by prompt length and feature; verify the current Google pricing table | Caching, tools, long context and regional rates may differ |
Gemma 4 | No Google token fee for self-hosted weights; infrastructure and hosted-provider rates vary | Self-hosting still incurs infrastructure and operations costs |
Token price is not cost per accepted result. Measure retries, tool calls, latency, infrastructure and reviewer time on the same task set.
Which Google model should you choose?
Requirement | Starting point | Why |
|---|---|---|
Highest current rank | Gemini 3.7 Flash | Highest Google placement in the current top eight |
Open weights or self-hosting | Gemma 4 | Review the exact license, checkpoint and hardware needs |
Restricted specialist work | No restricted model in this provider directory | Use generally available models and least-privilege controls |
Migration or reproduction | Gemini 3 Pro | Retained for historical and compatibility testing |
Lowest operational cost | Measure two or three eligible models | Headline token prices omit retries, tools, caching and human review |
Google models, explained
Gemini 3.7 Flash
Gemini 3.7 Flash was released August 13, 2026. It is listed as available with proprietary. The documented context window is 1,048,576 tokens, and the maximum output is 65,536 tokens.
- Best fit: Fast multimodal agents and high-volume applications.
- Modalities: Text, image, video, audio and PDF input; text output.
- Access: See the guide for current access routes.
- Pricing reference: $0.75 input / $3.75 output per million tokens, introductory.
- Current ranking: #7 with an Overall score of 78.8.
Read the complete Gemini 3.7 Flash guide for benchmarks, limitations, official sources and an evaluation framework.
Gemini 3 Deep Think
Gemini 3 Deep Think was released February 12, 2026 major upgrade. It is listed as available to google ai ultra subscribers with proprietary. The documented context window is 1 million tokens, and the maximum output is Product-managed; no standalone public API maximum.
- Best fit: difficult science, mathematics, research and engineering reasoning.
- Modalities: Multimodal input; text output through the Gemini app.
- Access: Gemini app for Google AI Ultra subscribers and selected research programs.
- Pricing reference: Included with eligible Google AI Ultra access; no standalone token price.
Read the complete Gemini 3 Deep Think guide for benchmarks, limitations, official sources and an evaluation framework.
Gemini 3 Pro
Gemini 3 Pro was released November 18, 2025. It is listed as available in selected products; api preview retired in favor of 3.1 pro with proprietary. The documented context window is 1,048,576 tokens, and the maximum output is 65,536 tokens.
- Best fit: historical multimodal reasoning comparisons and migration testing.
- Modalities: Text, image, video, audio and PDF input; text output.
- Access: Gemini products and legacy/partner surfaces; new API work should use Gemini 3.1 Pro.
- Pricing reference: Historical API pricing was tiered; use Gemini 3.1 Pro pricing for new integrations.
Read the complete Gemini 3 Pro guide for benchmarks, limitations, official sources and an evaluation framework.
Gemini 3.1 Pro
Gemini 3.1 Pro was released February 19, 2026. It is listed as preview with proprietary. The documented context window is 1,048,576 tokens, and the maximum output is 65,536 tokens.
- Best fit: multimodal reasoning, complex problem solving, software engineering and large mixed-media inputs.
- Modalities: Text, image, video, audio and PDF input; text output.
- Access: Gemini API, AI Studio, Vertex AI, Gemini Enterprise, Gemini app, NotebookLM, Gemini CLI and Android Studio.
- Pricing reference: Tiered Gemini API pricing varies by prompt length and feature; verify the current Google pricing table.
Read the complete Gemini 3.1 Pro guide for benchmarks, limitations, official sources and an evaluation framework.
Gemma 4
Gemma 4 was released 2026. It is listed as available; downloadable model family with open weights under the gemma license. The documented context window is Up to 256,000 tokens depending on variant, and the maximum output is Variant-specific within the context budget.
- Best fit: open multimodal agents, on-device work and size-flexible deployment.
- Modalities: Text and image input; selected variants support audio; text output.
- Access: Google AI tooling, Hugging Face and compatible local or cloud runtimes.
- Pricing reference: No Google token fee for self-hosted weights; infrastructure and hosted-provider rates vary.
Read the complete Gemma 4 guide for benchmarks, limitations, official sources and an evaluation framework.
How to evaluate Google models
Shortlist the Google models that meet your access, licensing and modality requirements. Freeze 20 to 50 representative tasks, then give each candidate the same prompts, tools, context, reasoning budget and retry limits. Record the exact model identifier because provider aliases can change.
Measure | Record | Decision use |
|---|---|---|
Task completion | Pass rate and rubric score | Establish whether the model meets the acceptance threshold |
Reliability | Repeated-run variance and recovery behavior | Avoid choosing from one lucky result |
Quality | Factuality, instruction following and reviewer acceptance | Separate polished output from correct output |
Tool use | Wrong calls, retries, permission errors and unsafe actions | Evaluate the model and agent harness together |
Efficiency | Wall time, tokens, caching, tools and review labor | Calculate cost per accepted result |
Governance | Retention, training, regional processing and audit logs | Confirm the deployment fits policy requirements |
Availability, versions and lifecycle
Google may expose different snapshots, effort settings, products and partner integrations under similar labels. Treat every model name as incomplete without an exact endpoint or checkpoint. Re-run regression tests after any model, system prompt, retrieval, tool or permission change.
- Available means a documented access route exists, not that every region or account has access.
- Preview models can change behavior, price or retirement dates before general availability.
- Open weights require an exact license and checkpoint review; “open” does not guarantee open training data or low operating cost.
- Restricted models require separate eligibility, safeguards and data-handling review.
- Legacy models remain useful for migration and reproduction but should not be the default for a new deployment.
Sources and update policy
Official Google model documentation is the provider-level starting point. Each linked model guide cites its own first-party launch page, model card, pricing reference and safety documentation.
Compare this provider with the complete Best AI Models directory.
Last verified September 2, 2026. The hub should be updated when the provider launches, retires, renames or reprices a model, changes context or output limits, alters licensing, or modifies regional availability.
Frequently asked questions
How many Google models are covered?
This hub covers 5: Gemini 3.7 Flash, Gemini 3.1 Pro, Gemini 3 Pro, Gemini 3 Deep Think, Gemma 4. Every model has a dedicated guide linked from the directory table and profile sections.
What is the best Google model?
Gemini 3.7 Flash is Google's highest-ranked model in the current AI Leaderboard, at number 7 with an Overall score of 78.8. Workload-specific testing can still favor another model.
Does Google offer open weights?
Yes. The directory identifies Gemma 4 as open-weight options. Review the exact license, downloadable artifact and serving requirements before deployment.
How current is the pricing?
Pricing references were verified September 2, 2026 from first-party documentation summarized in each model guide. Always recheck the provider before budgeting because cache, batch, long-context, tool and regional rates can change.
Should every Google model be tested?
No. Remove models that fail access, license, modality, context, latency or governance requirements first. Test the smallest credible shortlist on representative work.