Gemma 3 12B vs GPT-5
GPT-5 leads the LLM Stats Score 33.8 to 5.6. Gemma 3 12B is 45.8x cheaper per token.
Google · OpenAI · Updated for 2026
Which is better?
GPT-5 leads the overall LLM Stats Score 33.8 to 5.6, ranking #105 overall.
In the 3 individual benchmarks reported for both models, GPT-5 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Gemma 3 12B is roughly 45.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5 also accepts a larger context window (400,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemma 3 12B
- cost matters — it's about 45.8x cheaper per token
- you need open weights you can self-host or fine-tune
Choose GPT-5
- overall performance matters — it scores 33.8 and ranks #105 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- you process long inputs — it offers a 400,000 token context window
- you want the most recent training data — it shipped Aug 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
26 reported for Gemma 3 12B · 34 for GPT-5
Gemma 3 12B outperforms in 0 benchmarks, while GPT-5 is better at 3 benchmarks (GPQA, HumanEval, MATH).
GPT-5 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 3 12B ($0.05/1M tokens) is 25.0x cheaper than GPT-5 ($1.25/1M tokens).
For output processing, Gemma 3 12B ($0.15/1M tokens) is 66.7x cheaper than GPT-5 ($10.00/1M tokens).
In conclusion, GPT-5 is more expensive than Gemma 3 12B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5 accepts 400,000 input tokens compared to Gemma 3 12B's 131,072 tokens. Gemma 3 12B can generate longer responses up to 131,072 tokens, while GPT-5 is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both Gemma 3 12B and GPT-5 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 3 12B
GPT-5
License
Usage and distribution terms
Gemma 3 12B is licensed under Gemma, while GPT-5 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Gemma
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Gemma 3 12B was released on 2025-03-12, while GPT-5 was released on 2025-08-07.
GPT-5 is 5 months newer than Gemma 3 12B.
Mar 12, 2025
1.6 years ago
Aug 7, 2025
1.2 years ago
4mo newerKnowledge Cutoff
When training data ends
GPT-5 has a documented knowledge cutoff of 2024-09-30, while Gemma 3 12B's cutoff date is not specified.
We can confirm GPT-5's training data extends to 2024-09-30, but cannot make a direct comparison without Gemma 3 12B's cutoff date.
—
Sep 2024
Provider Availability
Gemma 3 12B is available from DeepInfra. GPT-5 is available from OpenAI.
Gemma 3 12B
GPT-5
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3 12B and GPT-5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3 12B vs GPT-5.