Neither wins outright: Google: Gemma 3 12B is the pick when you need tool / function calling, Inference.net: Schematron V2 Turbo when cost matters at scale.
| Spec | Google: Gemma 3 12B | Inference.net: Schematron V2 Turbo |
|---|---|---|
| Provider | Inference.net | |
| Input price (per 1M tokens) | $0.05 | $0.03 |
| Output price (per 1M tokens) | $0.15 | $0.15 |
| Blended price (3:1 input/output) | $0.08 | $0.06 |
| Cheaper than … of all models we track | 83% | 86% |
| Context window | 131K tokens (~197 pages) | 128K tokens (~192 pages) |
| Larger context than … of all models | 22% | 14% |
| Max output per response | 16K tokens (~12,300 words) | 8K tokens (~6,100 words) |
| Input types | text, image | text |
| Output types | text | text |
| Free variant | Yes | No |
| Listed since | 2025-03-13 | 2026-09-12 |
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: Gemma 3 12B | Inference.net: Schematron V2 Turbo | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $6.75 | $5.25 | Inference.net: Schematron V2 Turbo saves $1.50 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $7.50 | $5.10 | Inference.net: Schematron V2 Turbo saves $2.40 |
| 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) | $7.80 | $5.40 | Inference.net: Schematron V2 Turbo saves $2.40 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $4.90 | $3.30 | Inference.net: Schematron V2 Turbo saves $1.60 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $2.65 | $1.65 | Inference.net: Schematron V2 Turbo saves $1.00 |
| Capability | Google: Gemma 3 12B | Inference.net: Schematron V2 Turbo | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | — | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | — | — | spend extra tokens thinking before answering hard problems |
| Image input | ✓ Yes | — | read screenshots, charts and scanned pages |
| Audio input | — | — | take speech or audio directly |
| File / PDF input | — | — | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | — | — | 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.
| Date | Model | Input / 1M | Output / 1M |
|---|---|---|---|
| 2026-08-06 | Google: Gemma 3 12B | $0.05 | $0.15 |
Neither wins outright: Google: Gemma 3 12B is the pick when you need tool / function calling, Inference.net: Schematron V2 Turbo when cost matters at scale. In short: Google: Gemma 3 12B when you need tool / function calling, you need image input, you generate long outputs in one go, you want to prototype at zero cost; Inference.net: Schematron V2 Turbo when cost matters at scale, you want the newer model.
Inference.net: Schematron V2 Turbo is cheaper: $0.06 vs $0.08 per 1M tokens at a typical 3:1 input/output mix, 20% less. For 50,000 support conversations a month that is $5.25 against $6.75.
Google: Gemma 3 12B costs $0.05 per 1M input tokens and $0.15 per 1M output tokens; Inference.net: Schematron V2 Turbo costs $0.03 input and $0.15 output. Output tokens are billed separately, so long answers shift the gap.
Google: Gemma 3 12B: 131K tokens, about 197 pages, against 128K (about 192 pages) for Inference.net: Schematron V2 Turbo.
Tool calling — Google: Gemma 3 12B: yes, Inference.net: Schematron V2 Turbo: not advertised. JSON-schema structured output — Google: Gemma 3 12B: yes, Inference.net: Schematron V2 Turbo: yes.
Only Google: Gemma 3 12B accepts image input; Inference.net: Schematron V2 Turbo is text-only for input.
Google: Gemma 3 12B has a free variant (google/gemma-3-12b-it:free). Free variants usually carry tighter rate limits.
Google: Gemma 3 12B can write up to 16K tokens (about 12,300 words) per response; Inference.net: Schematron V2 Turbo up to 8K (about 6,100 words).
Google: Gemma 3 12B was listed on 2025-03-13; Inference.net: Schematron V2 Turbo on 2026-09-12.
Google: Gemma 3 12B: input price raised 20% ($0.04 → $0.05/1M), output price raised 13% ($0.13 → $0.15/1M) on 2026-08-06. Inference.net: Schematron V2 Turbo: price unchanged since we started tracking it on 2026-09-12.
Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...
Full Google: Gemma 3 12B specs →Schematron V2 Turbo is a 3B-parameter HTML-to-JSON extraction model from Inference.net. It prioritizes throughput for high-volume extraction workloads. Extraction instructions must be supplied through a JSON schema in response_format rather...
Full Inference.net: Schematron V2 Turbo specs →