Google: Gemma 3 12B vs OpenAI: gpt-oss-safeguard-20b
Neither wins outright: Google: Gemma 3 12B is the pick when cost matters at scale, OpenAI: gpt-oss-safeguard-20b when you need reasoning / thinking mode.
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
OpenAI: gpt-oss-safeguard-20b
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$6.75
$11.63
Google: Gemma 3 12B saves $4.88
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$7.50
$12.00
Google: Gemma 3 12B saves $4.50
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
$12.60
Google: Gemma 3 12B saves $4.80
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$4.90
$7.80
Google: Gemma 3 12B saves $2.90
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
$4.05
Google: Gemma 3 12B saves $1.40
Capabilities side by side
Capability
Google: Gemma 3 12B
OpenAI: gpt-oss-safeguard-20b
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
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.
OpenAI: gpt-oss-safeguard-20b: price unchanged since we started tracking it on 2026-03-10.
Date
Model
Input / 1M
Output / 1M
2026-08-06
Google: Gemma 3 12B
$0.05
$0.15
Which should you choose?
Choose Google: Gemma 3 12B if…
cost matters at scale — it is 43% cheaper on a typical 3:1 input/output mix ($6.75 vs $11.63 a month for 50,000 support chats)
you need image input — to read screenshots, charts and scanned pages; OpenAI: gpt-oss-safeguard-20b does not advertise it
you want to prototype at zero cost — a free variant is listed
Choose OpenAI: gpt-oss-safeguard-20b if…
you need reasoning / thinking mode — to spend extra tokens thinking before answering hard problems; Google: Gemma 3 12B does not advertise it
you generate long outputs in one go — up to 66K tokens (about 49,200 words) per response
you want the newer model — released 2025-10-29, 8 months after the other
Frequently asked questions
Is Google: Gemma 3 12B better than OpenAI: gpt-oss-safeguard-20b?
Neither wins outright: Google: Gemma 3 12B is the pick when cost matters at scale, OpenAI: gpt-oss-safeguard-20b when you need reasoning / thinking mode. In short: Google: Gemma 3 12B when cost matters at scale, you need image input, you want to prototype at zero cost; OpenAI: gpt-oss-safeguard-20b when you need reasoning / thinking mode, you generate long outputs in one go, you want the newer model.
Which is cheaper, Google: Gemma 3 12B or OpenAI: gpt-oss-safeguard-20b?
Google: Gemma 3 12B is cheaper: $0.08 vs $0.13 per 1M tokens at a typical 3:1 input/output mix, 43% less. For 50,000 support conversations a month that is $6.75 against $11.63.
How much do Google: Gemma 3 12B and OpenAI: gpt-oss-safeguard-20b cost per million tokens?
Google: Gemma 3 12B costs $0.05 per 1M input tokens and $0.15 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.
Which has the bigger context window, Google: Gemma 3 12B or OpenAI: gpt-oss-safeguard-20b?
Both take 131K tokens per request — roughly 197 pages of text.
Do Google: Gemma 3 12B and OpenAI: gpt-oss-safeguard-20b support function calling and JSON output?
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,...
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...