Neither wins outright: google/gemma-3-4b-it is the pick when cost matters at scale, OpenAI: gpt-oss-safeguard-20b when you need tool / function calling.
| Spec | google/gemma-3-4b-it | OpenAI: gpt-oss-safeguard-20b |
|---|---|---|
| Provider | OpenAI | |
| Input price (per 1M tokens) | $0.05 | $0.07 |
| Output price (per 1M tokens) | $0.10 | $0.30 |
| Blended price (3:1 input/output) | $0.06 | $0.13 |
| Cheaper than … of all models we track | 85% | 76% |
| Context window | 131K tokens (~197 pages) | 131K tokens (~197 pages) |
| Larger context than … of all models | 22% | 22% |
| Max output per response | 16K tokens (~12,300 words) | 66K tokens (~49,200 words) |
| Input types | text, image | text |
| Output types | text | text |
| Free variant | Yes | No |
| Listed since | 2025-03-13 | 2025-10-29 |
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-3-4b-it | OpenAI: gpt-oss-safeguard-20b | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $5.75 | $11.63 | google/gemma-3-4b-it saves $5.88 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $7.00 | $12.00 | google/gemma-3-4b-it saves $5.00 |
| 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) | $7.20 | $12.60 | google/gemma-3-4b-it saves $5.40 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $4.60 | $7.80 | google/gemma-3-4b-it saves $3.20 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $2.60 | $4.05 | google/gemma-3-4b-it saves $1.45 |
| Capability | google/gemma-3-4b-it | OpenAI: gpt-oss-safeguard-20b | 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 | — | ✓ Yes | 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 | ✓ Yes | — | 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 |
|---|---|---|---|
| 2026-10-28 | google/gemma-3-4b-it | $0.05 | $0.10 |
| 2026-10-20 | google/gemma-3-4b-it | $0.04 | $0.05 |
| 2026-08-06 | google/gemma-3-4b-it | $0.05 | $0.10 |
Neither wins outright: google/gemma-3-4b-it is the pick when cost matters at scale, OpenAI: gpt-oss-safeguard-20b when you need tool / function calling. In short: google/gemma-3-4b-it when cost matters at scale, you need image input, you need log-probabilities, you want to prototype at zero cost; OpenAI: gpt-oss-safeguard-20b when you need tool / function calling, you need reasoning / thinking mode, you generate long outputs in one go, you want the newer model.
google/gemma-3-4b-it is cheaper: $0.06 vs $0.13 per 1M tokens at a typical 3:1 input/output mix, 52% less. For 50,000 support conversations a month that is $5.75 against $11.63.
google/gemma-3-4b-it costs $0.05 per 1M input tokens and $0.10 per 1M output tokens; OpenAI: gpt-oss-safeguard-20b costs $0.07 input and $0.30 output. Output tokens are billed separately, so long answers shift the gap.
Both take 131K tokens per request — roughly 197 pages of text.
Tool calling — google/gemma-3-4b-it: not advertised, OpenAI: gpt-oss-safeguard-20b: yes. JSON-schema structured output — google/gemma-3-4b-it: yes, OpenAI: gpt-oss-safeguard-20b: yes.
Only google/gemma-3-4b-it accepts image input; OpenAI: gpt-oss-safeguard-20b is text-only for input.
google/gemma-3-4b-it has a free variant (google/gemma-3-4b-it:free). Free variants usually carry tighter rate limits.
google/gemma-3-4b-it can write up to 16K tokens (about 12,300 words) per response; OpenAI: gpt-oss-safeguard-20b up to 66K (about 49,200 words).
google/gemma-3-4b-it was listed on 2025-03-13; OpenAI: gpt-oss-safeguard-20b on 2025-10-29.
google/gemma-3-4b-it: input price raised 20% ($0.04 → $0.05/1M), output price raised 50% ($0.05 → $0.10/1M) on 2026-10-28 (3 price changes since 2026-03-10). OpenAI: gpt-oss-safeguard-20b: price unchanged since we started tracking it on 2026-03-10.
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-3-4b-it specs →gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b. This open-weight, 21B-parameter Mixture-of-Experts (MoE) model offers lower latency for safety tasks like content classification, LLM filtering, and trust...
Full OpenAI: gpt-oss-safeguard-20b specs →