Neither wins outright: Google: Gemini 3 Pro Preview is the pick when cost matters at scale, Meta: Muse Wonder when you need built-in web search.
| Spec | Google: Gemini 3 Pro Preview | Meta: Muse Wonder |
|---|---|---|
| Provider | Meta | |
| Input price (per 1M tokens) | $2.00 | $4.00 |
| Output price (per 1M tokens) | $12.00 | $20.00 |
| Blended price (3:1 input/output) | $4.50 | $8.00 |
| Cheaper than … of all models we track | 12% | 7% |
| 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) | 944K tokens (~707,800 words) |
| Input types | text, image, file, audio, video | text, image, video, file, audio |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2025-11-18 | 2026-10-12 |
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 | Meta: Muse Wonder | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $390 | $700 | Google: Gemini 3 Pro Preview saves $310 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $360 | $680 | Google: Gemini 3 Pro Preview saves $320 |
| 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 | $720 | Google: Gemini 3 Pro Preview saves $336 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $232 | $440 | Google: Gemini 3 Pro Preview saves $208 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $112 | $220 | Google: Gemini 3 Pro Preview saves $108 |
| Capability | Google: Gemini 3 Pro Preview | Meta: Muse Wonder | 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 | — | 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.
Neither wins outright: Google: Gemini 3 Pro Preview is the pick when cost matters at scale, Meta: Muse Wonder when you need built-in web search. In short: Google: Gemini 3 Pro Preview when cost matters at scale, you need seed (reproducible sampling); Meta: Muse Wonder when you need built-in web search, you generate long outputs in one go, you want the newer model.
Google: Gemini 3 Pro Preview is cheaper: $4.50 vs $8.00 per 1M tokens at a typical 3:1 input/output mix, 44% less. For 50,000 support conversations a month that is $390 against $700.
Google: Gemini 3 Pro Preview costs $2.00 per 1M input tokens and $12.00 per 1M output tokens; Meta: Muse Wonder costs $4.00 input and $20.00 output. Output tokens are billed separately, so long answers shift the gap.
Both take 1.0M tokens per request — roughly 1,573 pages of text.
Tool calling — Google: Gemini 3 Pro Preview: yes, Meta: Muse Wonder: yes. JSON-schema structured output — Google: Gemini 3 Pro Preview: yes, Meta: Muse Wonder: yes.
Yes, both accept image input.
No free variant is listed for either; both are pay-per-token.
Google: Gemini 3 Pro Preview can write up to 66K tokens (about 49,200 words) per response; Meta: Muse Wonder up to 944K (about 707,800 words).
Google: Gemini 3 Pro Preview was listed on 2025-11-18; Meta: Muse Wonder on 2026-10-12.
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 →Muse Wonder is a frontier reasoning model from Meta, designed for complex personal and professional agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with...
Full Meta: Muse Wonder specs →