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OPTERA LABS

Gemini 3.1 Pro VS Gemini 1.5 Pro

2026 Cost & Performance Comparison
Model A · Google

Gemini 3.1 Pro

gemini-3-1-pro

Intelligence Score89%
Cost / 1M Tokens$5.00

70% in · 30% out mix

Value Index(score÷cost)
17.8

Higher = better value

Speed

82/100

Context

2.0M

Tier

smart

Model B · Google

Gemini 1.5 Pro

gemini-1_5-pro

Intelligence Score87%
Cost / 1M Tokens$2.38

70% in · 30% out mix

Value Index(score÷cost)
36.6

Higher = better value

Speed

80/100

Context

1.0M

Tier

smart

IN-DEPTH ANALYSIS

Gemini 3.1 Pro vs Gemini 1.5 Pro: Detailed Comparison

Gemini 3.1 Pro is Google's mid-range-tier language model with a 2.0M-token context window, excelling at vision/multimodal. Gemini 1.5 Pro from Google is a mid-range-tier model supporting 1.0M tokens in context, with standout performance in vision/multimodal.

Gemini 1.5 Pro is the more cost-efficient option in this comparison — it costs up to 53% less than Gemini 3.1 Pro on a typical prompt/completion mix. Gemini 3.1 Pro is priced at $2.00/M input tokens and $12.00/M output tokens. Gemini 1.5 Pro costs $1.25/M input and $5.00/M output.

In independent benchmark evaluations, Gemini 3.1 Pro leads with coding scores of 88/100 and reasoning scores of 89/100, compared to Gemini 1.5 Pro's 82/100 in coding and 87/100 in reasoning.

Capability breakdown

Across the five core benchmark categories, here is how Gemini 3.1 Pro and Gemini 1.5 Pro stack up head to head:

coding
88
82
reasoning
89
87
data extraction
90
88
creative tasks
88
87
vision/multimodal
95
93

Best model by task

  • coding: Gemini 3.1 Pro wins with 88/100
  • reasoning: Gemini 3.1 Pro wins with 89/100
  • 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

At 10M + 2M per month, Gemini 3.1 Pro runs about $44.00 while Gemini 1.5 Pro runs about $22.50 — Gemini 1.5 Pro saves roughly $21.50 (49%) every month.

Gemini 3.1 Pro supports the larger context window at 2.0M tokens, useful for long-document analysis and large codebases. For latency-sensitive applications, Gemini 3.1 Pro has a speed score of 82/100 versus Gemini 1.5 Pro's 80/100.

Choose Gemini 1.5 Pro when cost efficiency is the priority; opt for Gemini 3.1 Pro when maximum performance is required. Gemini 3.1 Pro holds the edge in overall benchmark scores. Both models have distinct strengths — use the interactive calculator above to model costs for your exact token volume.

Benchmark Comparison

Head-to-head scores across 5 categories — sourced from official evals

CategoryGemini 3.1Gemini 1.5Winner

Coding

88
82
A

Reasoning

89
87
A

Extraction

90
88
A

Creative

88
87
A

Vision

95
93
A
Gemini 3.1 Pro: 5 wins
Gemini 1.5 Pro: 0 wins
Gemini 3.1 Pro leads overall

Speed Score

82/100vs80/100
GeminiGemini

Context Window

2000Kvs1000K
GeminiGemini

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!"

4 tokens

Business email

One typical email (~200 words)

~270 tokens

Code file

50-line Python script

~400 tokens

How to check your token usage

response.usage.total_tokens

Every 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

30.0M TOKENS
Prompt 70%Completion 30%

Gemini 3.1 Pro

$150.00/mo

$1,800.00/yr

$2/M in$12/M out
CHEAPER

Gemini 1.5 Pro

$71.25/mo

$855.00/yr

$1.25/M in$5/M out

Annual Savings

$945.00 saved per year

Gemini 1.5 Pro cheaper · $78.75/mo

Deep-Dive Audit — Gemini 3.1 Pro & Gemini 1.5 Pro

SURGICAL AUDIT LABA067AD04

Surgically Auditing: Deep Logic

Leakage Detected

3-YEAR STRATEGIC LOSS PROJECTION

$260.10

Without optimization protocols, current model choices will result in $86.70 capital loss per year.

EFFICIENCY SCORE

89%

Deep Logic

This model achieves a 89 benchmark score in this category.

CATEGORY GAP

9 pts

Distance from Leader

Competitive Landscape Analysis

Source: MMLU-Pro + GPQA Diamond (Apr 2026)

Category Champion: Claude Opus 4.6

According to MMLU-Pro + GPQA Diamond (Apr 2026) data, Claude Opus 4.6 provides the optimum balance for Deep Logic tasks.

Market Score

%98

Savings Rate

%52

Operational Prescription

  • Implement model cascading to optimize token spend.
  • Analyze complex_reasoning data to leverage local semantic caching.

COST AUDIT PROTOCOL

Overkill Detected

"Gemini 3.1 Pro is overpriced for this task type. Claude Opus 4.6 scores 98 in this category at a fraction of the cost."

Categorical Alternative Opportunity

"Claude Opus 4.6 leads this category with 98 points according to MMLU-Pro + GPQA Diamond (Apr 2026) data."

Inertia Tax Detected

"85% of traffic can be routed to cheaper models. Fast tier (DeepSeek V3) and Smart tier (o3-mini) can save $7.22/month."

3-Tier Intelligent Routing Architecture

52% SAVINGS VIA ROUTING
Fast Tier
50%

DeepSeek V3

IQ Score: 91/100

$50.40/yr

Smart Tier
35%

o3-mini

IQ Score: 97/100

$277.20/yr

Power Tier
15%

Claude Opus 4.6

IQ Score: 98/100

$648.00/yr

Fast Tier 50%Smart Tier 35%Power Tier 15%

Without tiered routing, you pay the 'Inertia Tax' — routing all traffic to the most expensive model regardless of task complexity. Tiered cascade eliminates $1,040.40/year in avoidable overhead.

Deep Logic — Model Cost / Quality Matrix

Source: MMLU-Pro + GPQA Diamond (Apr 2026)
ModelBenchmarkInput (per M)Output (per M)Annual Cost*Value Index
Claude Opus 4.6LEADER
98/100
$5.00$25.00$360.00
1/100
o3-mini
97/100
$1.10$4.40$66.00
6/100
DeepSeek R1
97/100
$0.55$2.19$32.88
12/100
GPT-5.2 Chat
96/100
$1.75$14.00$189.00
2/100
Claude 3.7 Sonnet
95/100
$3.00$15.00$216.00
2/100
Claude 3.5 Sonnet
93/100
$3.00$15.00$216.00
2/100
GPT-4.1
93/100
$2.00$8.00$120.00
3/100
DeepSeek V3
91/100
$0.28$0.42$8.40
45/100
Claude 3 Opus
90/100
$15.00$75.00$1,080.00
0/100
GPT-4o
90/100
$2.50$10.00$150.00
3/100
Gemini 3.1 ProSELECTED
89/100
$2.00$12.00$168.00
2/100
Gemini 2.0 Pro
88/100
$1.25$5.00$75.00
5/100
Llama 3.1 405B
88/100
$2.70$2.70$64.80
6/100
Gemini 1.5 Pro
87/100
$1.25$5.00$75.00
5/100
Mistral Large 2
86/100
$2.00$6.00$96.00
4/100
DeepSeek V3.2
83/100
$0.26$0.38$7.68
45/100
Gemini 2.0 Flash
81/100
$0.10$0.40$6.00
56/100
Claude 3.5 Haiku
80/100
$0.80$4.00$57.60
6/100
Llama 3 70B
79/100
$0.65$2.75$40.80
8/100
GPT-4o Mini
78/100
$0.15$0.60$9.00
36/100
Gemini 1.5 Flash
76/100
$0.07$0.30$4.50
70/100
GPT-5 NanoBEST VALUE
72/100
$0.10$0.15$3.00
100/100
Claude 3 Haiku
70/100
$0.25$1.25$18.00
16/100

* Annual cost for given volumes. Value Index = Score / Cost (Higher = Best Value).

Tactical Code Gen
// iOPTERA Surgical Routing Wrapper
const auditModel = async (prompt: string) => {
  const complexity = measureComplexity(prompt);
  
  // Tactical Cascade Logic
  if (complexity < 0.45) {
    // Redirect simple tasks to efficient model
    return await llm.call("iOPTERA Optimization", prompt); 
  }
  
  // High-latency routing for complex reasoning
  return await llm.call("Claude Opus 4.6", prompt);
};
READY TO DEPLOY IN Vercel Edge OR AWS Lambda

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