Choose Google: Gemini 3 Pro Preview if…
No advantage on the data we track — pick it for provider preference or output quality on your own prompts.
Google: Gemini 3 Pro Preview vs Google: Gemini 4 Argon
Google: Gemini 4 Argon comes out ahead on the data we track: 3 advantages and none for Google: Gemini 3 Pro Preview.
Key numbers
| Spec | Google: Gemini 3 Pro Preview | Google: Gemini 4 Argon |
|---|---|---|
| Provider | ||
| Input price (per 1M tokens) | $2.00 | $2.00 |
| Output price (per 1M tokens) | $12.00 | $10.00 |
| Blended price (3:1 input/output) | $4.50 | $4.00 |
| Cheaper than … of all models we track | 12% | 15% |
| Context window | 1.0M tokens (~1,573 pages) | 1.0M tokens (~1,573 pages) |
| Larger context than … of all models | 81% | 81% |
| Max output per response | 66K tokens (~49,200 words) | 66K tokens (~49,200 words) |
| Input types | text, image, file, audio, video | audio, file, image, text, video |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2025-11-18 | 2026-10-13 |
What it costs for real workloads
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
| Workload (per month) | Google: Gemini 3 Pro Preview | Google: Gemini 4 Argon | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $390 | $350 | Google: Gemini 4 Argon saves $40.00 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $360 | $340 | Google: Gemini 4 Argon saves $20.00 |
| Coding / tool-using agent 2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens) | $384 | $360 | Google: Gemini 4 Argon saves $24.00 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $232 | $220 | Google: Gemini 4 Argon saves $12.00 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $112 | $110 | Google: Gemini 4 Argon saves $2.00 |
Capabilities side by side
| Capability | Google: Gemini 3 Pro Preview | Google: Gemini 4 Argon | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | ✓ Yes | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | ✓ Yes | ✓ Yes | spend extra tokens thinking before answering hard problems |
| Image input | ✓ Yes | ✓ Yes | read screenshots, charts and scanned pages |
| Audio input | ✓ Yes | ✓ Yes | take speech or audio directly |
| File / PDF input | ✓ Yes | ✓ Yes | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | — | ✓ Yes | answer from live web results |
| Seed (reproducible sampling) | ✓ Yes | ✓ Yes | repeat a generation for tests and evals |
| Log-probabilities | — | — | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Price history
- Google: Gemini 3 Pro Preview: price unchanged since we started tracking it on 2026-03-10.
- Google: Gemini 4 Argon: price unchanged since we started tracking it on 2026-10-14.
Which should you choose?
Choose Google: Gemini 4 Argon if…
- cost matters at scale — it is 11% cheaper on a typical 3:1 input/output mix ($350 vs $390 a month for 50,000 support chats)
- you need built-in web search — to answer from live web results; Google: Gemini 3 Pro Preview does not advertise it
- you want the newer model — released 2026-10-13, 11 months after the other
Frequently asked questions
Is Google: Gemini 3 Pro Preview better than Google: Gemini 4 Argon?
Google: Gemini 4 Argon comes out ahead on the data we track: 3 advantages and none for Google: Gemini 3 Pro Preview.
Which is cheaper, Google: Gemini 3 Pro Preview or Google: Gemini 4 Argon?
Google: Gemini 4 Argon is cheaper: $4.00 vs $4.50 per 1M tokens at a typical 3:1 input/output mix, 11% less. For 50,000 support conversations a month that is $350 against $390.
How much do Google: Gemini 3 Pro Preview and Google: Gemini 4 Argon cost per million tokens?
Google: Gemini 3 Pro Preview costs $2.00 per 1M input tokens and $12.00 per 1M output tokens; Google: Gemini 4 Argon costs $2.00 input and $10.00 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Google: Gemini 3 Pro Preview or Google: Gemini 4 Argon?
Both take 1.0M tokens per request — roughly 1,573 pages of text.
Do Google: Gemini 3 Pro Preview and Google: Gemini 4 Argon support function calling and JSON output?
Tool calling — Google: Gemini 3 Pro Preview: yes, Google: Gemini 4 Argon: yes. JSON-schema structured output — Google: Gemini 3 Pro Preview: yes, Google: Gemini 4 Argon: yes.
Can Google: Gemini 3 Pro Preview or Google: Gemini 4 Argon read images?
Yes, both accept image input.
Is Google: Gemini 3 Pro Preview or Google: Gemini 4 Argon free to use?
No free variant is listed for either; both are pay-per-token.
What is the maximum output length of Google: Gemini 3 Pro Preview and Google: Gemini 4 Argon?
Google: Gemini 3 Pro Preview can write up to 66K tokens (about 49,200 words) per response; Google: Gemini 4 Argon up to 66K (about 49,200 words).
When were Google: Gemini 3 Pro Preview and Google: Gemini 4 Argon released?
Google: Gemini 3 Pro Preview was listed on 2025-11-18; Google: Gemini 4 Argon on 2026-10-13.
About the two models
Google: Gemini 3 Pro Preview
Gemini 3 Pro is Google’s flagship frontier model for high-precision multimodal reasoning, combining strong performance across text, image, video, audio, and code with a 1M-token context window. Reasoning Details must be preserved when using multi-turn tool calling, see our docs here: https://openrouter.ai/docs/use-cases/reasoning-tokens#preserving-reasoning-blocks. It delivers state-of-the-art benchmark results in general reasoning, STEM problem solving, factual QA, and multimodal understanding, including leading scores on LMArena, GPQA Diamond, MathArena Apex, MMMU-Pro, and Video-MMMU. Interactions emphasize depth and interpretability: the model is designed to infer intent with minimal prompting and produce direct, insight-focused responses. Built for advanced development and agentic workflows, Gemini 3 Pro provides robust tool-calling, long-horizon planning stability, and strong zero-shot generation for complex UI, visualization, and coding tasks. It excels at agentic coding (SWE-Bench Verified, Terminal-Bench 2.0), multimodal analysis, and structured long-form tasks such as research synthesis, planning, and interactive learning experiences. Suitable applications include autonomous agents, coding assistants, multimodal analytics, scientific reasoning, and high-context information processing.
Full Google: Gemini 3 Pro Preview specs →Google: Gemini 4 Argon
Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...
Full Google: Gemini 4 Argon specs →