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Gemini 3.8 Flash (high) vs GPT-6.1 Sol (xhigh)

The average score is effectively tied at 9.9 vs 9.9. GPT-6.1 Sol (xhigh) has the lower benchmark cost at $1.156 vs $1.595. GPT-6.1 Sol (xhigh) is faster at 31.94s vs 37.19s, with pass rates of 98.5% vs 97.0%.

Last updated at: 2026-09-29

Compared models

Rank
#2
Total Output Tokens
408,188
Response Time (avg)
37.19s
Total Cost
$1.595
Rank
#6
Total Output Tokens
99,719
Response Time (avg)
31.94s
Total Cost
$1.156
Recommended model GPT-6.1 Sol (xhigh)

It has the strongest score in this comparison (9.9) and the best overall balance of cost and response time across all 2 models.

Detailed comparison

Metric Gemini 3.8 Flash Gemini 3.8 Flash high Release: 2026-09-02 GPT-6.1 Sol GPT-6.1 Sol xhigh Release: 2026-09-29
Score 9.9 9.9
Rank #2 #6
Reliability 10.0 10.0
Consistency 9.6 9.6
Attempts 66/66 66/66
Tests Correct
Attempt pass rate 98.5% 97.0%
Flaky tests 1 1
Total Runs 66 66
Cost per result 7.592 5.504
Total Cost $1.595 $1.156
Input Price $0.750 / 1M $2.000 / 1M
Output Price $3.750 / 1M $10.000 / 1M
Total Input Tokens 84,593 79,232
Output Tokens 10,517 4,811
Reasoning Tokens 397,671 94,908
Response Time (avg) 37.19s 31.94s
Response Time (max) 177.08s 491.85s
Response Time (total) 818.19s 702.66s
Parameters ~500B total (~20B active) ~2T total (~150B active)
Availability Closed Closed

Model generation showcase

Hamster playing table tennis

Prompt: Create a detailed SVG illustration of a hamster playing table tennis.

#2 Gemini 3.8 Flash

high
Cost
$0.077
Time
129.1s
Tokens
20,373 tok

#6 GPT-6.1 Sol

xhigh
Cost
$0.147
Time
279.4s
Tokens
14,790 tok

Top Models by Score

Score vs Total Cost

Response Time (avg)

Score vs Response Time (avg)

Total Output Tokens

Score vs Total Output Tokens

Category Breakdown

Coding Score Consistency Attempt pass rate Flaky tests Tests Correct Response Time (avg) Input Tokens Output Tokens Reasoning Tokens
Gemini 3.8 Flash 10.0 10.0 100.0% 0 29.30s 8,118 462 50,196
GPT-6.1 Sol 10.0 10.0 100.0% 0 10.65s 7,302 393 4,483

Quick Compare

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