Cost and performance comparison
Gemini 3.1 Pro vs o3-mini
Model AGoogle
Gemini 3.1 Pro
- Cost / 1M Tokens
- $5.00
- 70% in · 30% out mix
- Value Index (score÷cost)
- 18.4
- Higher = better value
- Speed
- 82/100
- Context
- 1.0M
- Tier
- Smart Tier
List price from the Google pricing page, verified October 19, 2026.
Check the sourceModel BOpenAI
o3-mini
- Cost / 1M Tokens
- $2.09
- 70% in · 30% out mix
- Value Index (score÷cost)
- 44.5
- Higher = better value
- Speed
- 78/100
- Context
- 200K
- Tier
- Smart Tier
List price from the OpenAI pricing page, verified September 30, 2026.
Check the sourceIn-depth analysis
Gemini 3.1 Pro vs o3-mini: Detailed Comparison
Gemini 3.1 Pro is Google's mid-range-tier language model with a 1.0M-token context window, excelling at vision/multimodal. o3-mini from OpenAI is a mid-range-tier model supporting 200K tokens in context, with standout performance in reasoning.
o3-mini is both the cheaper and the stronger model here — for the same text it costs 57% less than Gemini 3.1 Pro and still leads on combined coding and reasoning by 4 points. There is no tradeoff to weigh on this pair: unless you need something specific from Gemini 3.1 Pro, the cheaper model is simply the better one. Gemini 3.1 Pro is priced at $2.00/M input tokens and $12.00/M output tokens. o3-mini costs $1.10/M input and $4.40/M output.
On iOPTERA's editorial scores, o3-mini leads with 88/100 for coding and 93/100 for reasoning, against Gemini 3.1 Pro's 88/100 and 89/100.
Capability breakdown
Across the five core benchmark categories, here is how Gemini 3.1 Pro and o3-mini stack up head to head:
Best model by task
- reasoning: o3-mini wins with 93/100
- data extraction: Gemini 3.1 Pro wins with 90/100
- creative tasks: Gemini 3.1 Pro wins with 88/100
- vision/multimodal: Gemini 3.1 Pro wins with 95/100
Estimated monthly cost at scale
For 10M + 2M tokens of text a month (counted the way OpenAI's tokenizer counts), Gemini 3.1 Pro runs about $42.68 while o3-mini runs about $19.80 — o3-mini saves roughly $22.88 (54%) every month.
What actually decides it
Gemini 3.1 Pro and o3-mini come from different labs, which means different tokenizers, different API shapes, and a second vendor relationship. The same English text does not produce the same token count on both, so a price-per-million comparison understates the difference — measure your own prompts on each before treating the headline rates as the full story.
Gemini 3.1 Pro and o3-mini are 13 months apart, which is more than one generation in this market. Benchmark comparisons across that gap flatter the older model: it was measured against the evaluations that existed at the time. Treat o3-mini's scores as a floor for what it does well and be sceptical of a close-looking result.
The context gap is the largest single difference on this pair: Gemini 3.1 Pro takes 1.0M tokens against 200K for o3-mini, roughly 5.2x. That is the difference between feeding in a whole repository or a full contract set and having to chunk it. If your work involves documents you cannot split cleanly, this decides it on its own.
Throughput is close enough to ignore — 82/100 versus 78/100. Neither model will feel noticeably quicker in an interactive product, so latency is not a reason to choose between them.
o3-mini wins this comparison outright — cheaper and stronger. Choose Gemini 3.1 Pro only if it has a specific capability you need; on price and benchmarks it is behind on both.
What you actually pay
The list price is only the start. Prompt caching, batch processing and long prompts change the bill, and each provider sets them differently. Prices per 1M tokens.
| Pricing term | Gemini 3.1 Pro | o3-mini |
|---|---|---|
| List price (input / output) | $2.00 / $12.00 | $1.10 / $4.40 |
| Cached input | $0.2010% of the input price | — |
| Batch API | 50% off input and output | — |
| Long prompts | Over 200K tokens: $4.00 / $18.00 | — |
| Input with 80% cache hits | $0.56 | — |
The last row assumes 80% of input tokens are read from the cache, as in a chat app that re-sends a long system prompt or RAG over the same documents. Cache-write and storage charges are not included.
Gemini also bills cache storage by the hour.
Checked on October 8, 2026 against the pricing pages of Google, OpenAI.
Capability scores
iOPTERA editorial scores across 5 categories — informed by public benchmarks, not measured by us
Coding
Reasoning
Extraction
Creative
Vision
Speed Score
Context Window
What Is a Token?
Models don't read words — they process tokens.
A token is roughly 4 characters of English text (~¾ of a word). Your API bill is priced per million tokens — understanding this directly reduces your costs.
Short phrase
"Hello, world!"
- Gemini 3.1 Pro
- $0.78
- o3-mini
- $0.44
Business email
One typical email (~200 words)
- Gemini 3.1 Pro
- $52.38
- o3-mini
- $29.70
Code file
50-line Python script
- Gemini 3.1 Pro
- $77.60
- o3-mini
- $44.00
Prices shown are for 100,000 runs of each workload — one run costs a fraction of a cent on both Gemini 3.1 Pro and o3-mini, so the number only becomes meaningful at production volume. Input tokens only; add your output volume in the calculator below.
How to check your token usage
response.usage.total_tokensEvery API response includes a usage object. Sum total_tokens across all calls to get your monthly figure, then use the calculator below.
Your Cost Calculator
Enter your actual monthly token usage to see real savings
Quick Presets
Gemini 3.1 Pro
$145.50/mo
$1,746.00/yr
o3-mini
$62.70/mo
$752.40/yr
Annual Savings
$993.60 saved per year
o3-mini cheaper · $82.80/mo
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