Gemini 3.1 Pro just became the best value in AI APIs. It matches GPT-5.4 on most benchmarks while costing 20-40% less. But benchmarks are benchmarks — I wanted to see how they compare on real work.
I ran both models on 500 identical tasks across 4 categories and tracked quality, speed, and actual cost. Here's the raw data.
The Test Setup
- 500 tasks total: 150 coding, 100 reasoning/math, 150 document analysis, 100 creative writing
- Identical prompts sent to both models
- Quality scored 1-5 by human evaluation (me + 2 colleagues, averaged)
- Cost tracked per-task including cache hits
Results Summary
| Category | GPT-5.4 Quality | Gemini 3.1 Pro Quality | Winner | GPT-5.4 Cost | Gemini Cost | Cost Savings |
|---|---|---|---|---|---|---|
| Coding (150 tasks) | 4.3 | 4.1 | GPT | $18.75 | $13.20 | 30% |
| Reasoning (100 tasks) | 4.1 | 4.2 | Gemini | $14.50 | $10.80 | 26% |
| Document analysis (150 tasks) | 4.0 | 4.2 | Gemini | $22.50 | $14.40 | 36% |
| Creative writing (100 tasks) | 4.4 | 4.0 | GPT | $12.00 | $8.40 | 30% |
| Overall | 4.2 | 4.1 | Tie | $67.75 | $46.80 | 31% |
GPT-5.4 wins on quality by 0.1 points. Gemini wins on cost by 31%. That's the entire story.
Category Breakdown
Coding: GPT-5.4 Wins (Barely)
GPT-5.4 scored 4.3 vs Gemini's 4.1 on coding tasks. The difference showed up mainly in:
- Multi-file refactoring: GPT was better at understanding relationships across files
- Edge case handling: GPT caught more edge cases in generated code
- Simple functions: Essentially identical quality — the gap only appears on complex tasks
If your coding tasks are straightforward (CRUD, API integrations, utility functions), you won't notice a quality difference. Save the 30%.
Reasoning: Gemini Wins
Gemini scored 4.2 vs GPT's 4.1 on math and logic tasks. The surprise: Gemini's "thinking mode" produced more thorough chain-of-thought reasoning without the separate billing that OpenAI's o3 charges.
Gemini includes reasoning tokens in the standard output price ($12/M). OpenAI charges reasoning as hidden output tokens on o3 at $8/M — and those tokens can 3-10x your bill.
Document Analysis: Gemini Wins Clearly
This is where Gemini's 2M context window pays off. For documents over 200K tokens:
- GPT-5.4: Hits the 272K surcharge → 2x input pricing → $5.00/M
- Gemini 3.1 Pro: Flat $2.00/M all the way to 2M tokens (no surcharge on Pro)
On a 500K-token document, Gemini costs $1.00. GPT-5.4 costs $2.50. Same quality. 60% savings.
Creative Writing: GPT Wins
GPT-5.4 scored 4.4 vs Gemini's 4.0 — the biggest quality gap in any category. GPT produces more natural, varied prose. Gemini's writing is competent but slightly formulaic.
If writing quality is your primary need, GPT is worth the premium.
The Pricing Math
| Metric | GPT-5.4 | Gemini 3.1 Pro | Difference |
|---|---|---|---|
| Input/M | $2.50 | $2.00 | Gemini 20% cheaper |
| Output/M | $15.00 | $12.00 | Gemini 20% cheaper |
| Cache hit/M | $0.25 | $0.20 | Gemini 20% cheaper |
| Long-context surcharge | 2x past 272K | 2x past 200K* | GPT has higher threshold |
| Batch pricing | $1.25/$7.50 | Available | Similar |
| Context window | 1.1M | 2M | Gemini 1.8x more |
*Gemini 3.1 Pro Preview currently has no long-context surcharge on some tiers. Verify current pricing.
At 10K tasks/month (my production volume):
- GPT-5.4: ~$1,350/month
- Gemini 3.1 Pro: ~$940/month
- Annual savings: $4,920
That's enough to pay for another engineer's tooling budget. For a 0.1 point quality difference.
When to Use Which
| Use Case | Pick This | Why |
|---|---|---|
| Code generation (complex) | GPT-5.4 | 0.2 point quality edge matters for production code |
| Code generation (simple) | Gemini 3.1 Pro | Same quality, 30% cheaper |
| Document analysis | Gemini 3.1 Pro | 2M context, no surcharge, 36% cheaper |
| Math/reasoning | Gemini 3.1 Pro | Slightly better quality + built-in thinking mode |
| Creative writing | GPT-5.4 | Noticeably better prose quality |
| Cost-sensitive production | Gemini 3.1 Pro | 20-40% cheaper across the board |
| Need >1M context | Gemini 3.1 Pro | Only option with 2M context |
| Need computer use | GPT-5.4 | Gemini doesn't have this |
The Budget Option Everyone Forgets
Neither GPT-5.4 nor Gemini Pro is the cheapest option. DeepSeek V4 at $0.30/$0.50 scores 81% on SWE-bench (higher than both) and costs 8-30x less.
For the 500 tasks I tested, DeepSeek would have cost approximately $4.80 total. Compare that to GPT's $67.75 or Gemini's $46.80.
The quality gap is real but small — DeepSeek scored 4.0 overall vs GPT's 4.2 in my limited testing. If your workload tolerates that 0.2 point difference, the cost savings are enormous.
My Recommendation
Default to Gemini 3.1 Pro for most production workloads. The 0.1 point quality difference vs GPT-5.4 doesn't justify a 31% cost premium for the majority of tasks.
Switch to GPT-5.4 for: complex code generation, creative writing, and anything requiring computer use.
Switch to DeepSeek V4 for: cost-sensitive batch processing where a small quality trade-off is acceptable.
Best of all: Use a unified API gateway that lets you route different task types to different models automatically. One API key, one bill, optimal model per task.
Full Data
The complete benchmark data, pricing tables for all major models, and cost-per-task calculations:
👉 Gemini 2.5 Pro Review — Full Benchmark and Pricing Analysis
👉 GPT-5.4 vs Claude Sonnet 4.6 — Head-to-Head
👉 Every LLM Ranked by Real Cost Per Task
500 tasks tested, April 2026. Quality scores are subjective human evaluations, not benchmark proxies. Your results may differ based on prompt style and task specifics.
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