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How many bananas can I buy for $10?

Overview

31-45 27.7% 28 of 74 models agree
31-45 28%
16-30 26%
refusal 20%
31-45 · 27.7%
16-30 · 26%
0-15 · 9%
46-60 · 8.6%
61-100 · 1.3%
other · 5.2%
hedge · 1.8%
refusal · 20.4%

By country of origin

Each country averages the models of the companies headquartered there, one vote per model.
United States
41 models
31-45 29%
16-30 28%
refusal 22%
China
26 models
31-45 32%
16-30 21%
46-60 16%
refusal 19%
South Korea
4 models
16-30 28%
0-15 38%
hedge 10%
refusal 13%
France
3 models
16-30 38%
0-15 42%
refusal 18%

By company

Each company averages its own models, one vote per model.
OpenAI
12 models
31-45 25%
16-30 25%
0-15 11%
refusal 29%
Anthropic
10 models
31-45 41%
16-30 28%
refusal 14%
Google
7 models
31-45 30%
16-30 30%
refusal 30%
Qwen
6 models
31-45 39%
46-60 33%
refusal 18%
Z.ai
6 models
31-45 23%
46-60 17%
other 34%
refusal 13%
MiniMax
4 models
31-45 20%
16-30 48%
46-60 13%
refusal 15%
MoonshotAI
4 models
31-45 60%
16-30 16%
refusal 14%
Upstage
4 models
16-30 28%
0-15 38%
hedge 10%
refusal 13%
xAI
4 models
31-45 20%
16-30 30%
46-60 13%
refusal 24%
DeepSeek
3 models
16-30 16%
refusal 67%
Inception
3 models
31-45 37%
16-30 37%
refusal 17%
Mistral
3 models
16-30 38%
0-15 42%
refusal 18%
+ 8 with fewer than 3 models
IBM
1 model
16-30 50%
refusal 50%
Jared Palmer
1 model
31-45 50%
16-30 10%
0-15 20%
46-60 20%
NVIDIA
1 model
16-30 38%
hedge 31%
StepFun
1 model
31-45 14%
16-30 71%
46-60 14%
Tencent
1 model
31-45 33%
16-30 25%
0-15 33%
ThinkingMachines
1 model
31-45 40%
16-30 10%
46-60 15%
61-100 10%
hedge 20%
TypeSafe
1 model
16-30 40%
0-15 60%
Xiaomi
1 model
31-45 64%
16-30 27%

By model release quarter

Each quarter averages only the models released in that quarter. 1 model excluded (no release date on record).
0%50%100% 31-4516-30refusal Q3 2024n=1 Q2 2025n=3 Q3 n=3 Q4 n=5 Q1 2026n=18 Q2 n=23 Q3 n=20 2024 Q3 · 1 model 16-30: 67% refusal: 33% 2025 Q2 · 3 models 16-30: 21% 0-15: 26% 46-60: 2% other: 4% refusal: 47% 2025 Q3 · 3 models 31-45: 5% 16-30: 26% 0-15: 13% 46-60: 2% 61-100: 2% other: 3% refusal: 48% 2025 Q4 · 5 models 31-45: 15% 16-30: 34% 0-15: 10% 46-60: 6% other: 21% refusal: 13% 2026 Q1 · 18 models 31-45: 27% 16-30: 22% 0-15: 14% 46-60: 9% 61-100: 2% other: 6% hedge: 2% refusal: 18% 2026 Q2 · 23 models 31-45: 28% 16-30: 27% 0-15: 1% 46-60: 12% 61-100: 1% other: 4% hedge: 2% refusal: 25% 2026 Q3 · 20 models 31-45: 40% 16-30: 25% 0-15: 10% 46-60: 7% 61-100: 1% other: 2% hedge: 3% refusal: 11%
31-45
16-30
0-15
46-60
61-100
other
hedge
refusal
+ Show data
Quarter Models 31-4516-300-1546-6061-100otherhedgerefusal
2024 Q3 1 0%67%0%0%0%0%0%33%
2025 Q2 3 0%21%26%2%0%4%0%47%
2025 Q3 3 5%26%13%2%2%3%0%48%
2025 Q4 5 15%34%10%6%0%21%0%13%
2026 Q1 18 27%22%14%9%2%6%2%18%
2026 Q2 23 28%27%1%12%1%4%2%25%
2026 Q3 20 40%25%10%7%1%2%3%11%

Author's note

Tests grounded real-world price intuition rather than opinion — is the model's sense of everyday costs realistic? (Actual US grocery prices put this around 40-60 bananas.)

User message(s)

How many bananas can I buy for $10?
+ 2 more prompts
If I have $10 to spend, how many bananas could I buy?
Roughly how many bananas would $10 get me?

74 models

Anthropic

anthropic/claude-sonnet-5.5 (10 runs) · consistency 44.4

31-45 60%
16-30 40%

anthropic/claude-opus-5.5 (10 runs) · consistency 77.8

31-45 90%
46-60 10%

anthropic/claude-opus-5 (20 runs) · consistency 36.1

31-45 70%
46-60 25%

anthropic/claude-sonnet-5 (19 runs) · consistency 77.8

16-30 79%
refusal 16%

anthropic/claude-opus-4.8 (5 runs)

31-45 60%
16-30 20%
refusal 20%

anthropic/claude-opus-4.7 (20 runs) · consistency 50

31-45 45%
16-30 50%

anthropic/claude-sonnet-4.6 (20 runs) · consistency 13.9

31-45 15%
16-30 25%
0-15 25%
refusal 30%

anthropic/claude-opus-4.6 (15 runs) · consistency 50

31-45 67%
61-100 33%

anthropic/claude-haiku-4.5 (18 runs) · consistency 44.4

16-30 61%
0-15 39%

anthropic/claude-sonnet-4.5 (8 runs)

0-15 25%
refusal 75%

DeepSeek

deepseek/deepseek-v4-flash (13 runs) · consistency 36.1

31-45 23%
16-30 23%
refusal 46%

deepseek/deepseek-v4-pro (1 runs)

refusal 100%

deepseek/deepseek-v3.2 (16 runs) · consistency 50

16-30 25%
0-15 13%
refusal 56%

Google

google/gemini-3.5-flash (15 runs) · consistency 77.8

31-45 80%
16-30 13%

google/gemini-3.1-flash-lite (20 runs) · consistency 33.3

31-45 45%
16-30 45%

google/gemma-4-26b-a4b-it (13 runs) · consistency 27.8

31-45 23%
16-30 31%
refusal 46%

google/gemma-4-31b-it (17 runs) · consistency 44.4

16-30 35%
refusal 59%

google/gemini-3-flash-preview (15 runs) · consistency 27.8

31-45 47%
16-30 33%
46-60 20%

google/gemini-2.5-flash-lite (20 runs) · consistency 13.9

31-45 10%
16-30 35%
0-15 15%
other 10%
refusal 20%

google/gemini-2.5-flash (5 runs)

16-30 20%
refusal 80%

IBM

ibm-granite/granite-4.1-8b (20 runs) · consistency 44.4

16-30 50%
refusal 50%

Inception

inception/mercury-decide:free (10 runs) · consistency 77.8

16-30 90%
61-100 10%

inception/mercury-2.5 (10 runs) · consistency 61.1

31-45 70%
16-30 20%
refusal 10%

inception/mercury-2 (10 runs) · consistency 25

31-45 40%
other 10%
hedge 10%
refusal 40%

Jared Palmer

jaredpalmer/kev-4b (10 runs) · consistency 30.6

31-45 50%
16-30 10%
0-15 20%
46-60 20%

MiniMax

minimax/minimax-m3 (13 runs) · consistency 19.4

31-45 15%
16-30 38%
refusal 23%

minimax/minimax-m2.7 (11 runs) · consistency 27.8

31-45 36%
16-30 36%
refusal 27%

minimax/minimax-m2.5 (3 runs)

16-30 67%
46-60 33%

minimax/minimax-m2.1 (10 runs) · consistency 30.6

31-45 30%
16-30 50%
46-60 10%
refusal 10%

Mistral

mistralai/mistral-small-2603 (20 runs) · consistency 44.4

16-30 10%
0-15 70%
refusal 20%

mistralai/mistral-small-3.2-24b-instruct (16 runs) · consistency 44.4

16-30 38%
0-15 56%

mistralai/mistral-nemo (3 runs)

16-30 67%
refusal 33%

MoonshotAI

moonshotai/kimi-k3 (20 runs) · consistency 61.1

31-45 75%
46-60 15%

moonshotai/kimi-k2.7-code (12 runs) · consistency 33.3

31-45 50%
16-30 17%
refusal 25%

moonshotai/kimi-k2.6 (9 runs) · consistency 30.6

31-45 56%
16-30 22%
46-60 11%
refusal 11%

moonshotai/kimi-k2.5 (5 runs)

31-45 60%
16-30 20%
refusal 20%

NVIDIA

nvidia/nemotron-3-ultra-550b-a55b (13 runs) · consistency 19.4

16-30 38%
hedge 31%

OpenAI

openai/gpt-6.1-sol (10 runs) · consistency 50

31-45 30%
16-30 70%

openai/gpt-6-luna (10 runs) · consistency 33.3

31-45 50%
16-30 10%
refusal 40%

openai/gpt-6-sol (10 runs) · consistency 36.1

31-45 50%
16-30 40%
refusal 10%

openai/gpt-5.6-luna (6 runs)

31-45 50%
16-30 17%
refusal 33%

openai/gpt-5.6-sol (13 runs) · consistency 44.4

31-45 62%
other 15%
refusal 15%

openai/gpt-5.6-terra (17 runs) · consistency 19.4

31-45 12%
46-60 18%
refusal 53%

openai/gpt-5.5 (12 runs) · consistency 13.9

31-45 17%
16-30 17%
other 25%
refusal 25%

openai/gpt-5.4-mini (18 runs) · consistency 25

16-30 28%
0-15 22%
other 11%
refusal 39%

openai/gpt-5.4-nano (19 runs) · consistency 25

16-30 32%
0-15 16%
refusal 47%

openai/gpt-5.4 (15 runs) · consistency 44.4

16-30 33%
0-15 67%

openai/gpt-5.3-chat (11 runs) · consistency 22.2

31-45 27%
16-30 36%
other 18%
refusal 18%

openai/gpt-4.1-mini (18 runs) · consistency 44.4

0-15 22%
other 11%
refusal 61%

Qwen

qwen/qwen3.7-max (12 runs) · consistency 50

31-45 42%
46-60 50%

qwen/qwen3.6-flash (15 runs) · consistency 50

31-45 33%
refusal 60%

qwen/qwen3.6-max-preview (2 runs)

46-60 100%

qwen/qwen3.5-122b-a10b (2 runs)

31-45 50%
46-60 50%

qwen/qwen3.5-flash-02-23 (2 runs)

31-45 100%

qwen/qwen3-235b-a22b-2507 (16 runs) · consistency 36.1

16-30 44%
refusal 50%

StepFun

stepfun/step-3.7-flash (7 runs)

31-45 14%
16-30 71%
46-60 14%

Tencent

tencent/hy3:free (12 runs) · consistency 19.4

31-45 33%
16-30 25%
0-15 33%

ThinkingMachines

thinkingmachines/inkling (20 runs) · consistency 22.2

31-45 40%
16-30 10%
46-60 15%
61-100 10%
hedge 20%

TypeSafe

typesafe/jev-1.13 (10 runs) · consistency 44.4

16-30 40%
0-15 60%

Upstage

upstage/solar-decide (10 runs) · consistency 100

0-15 100%

upstage/solar-mini4 (10 runs) · consistency 30.6

31-45 10%
16-30 60%
0-15 20%
hedge 10%

upstage/solar-pro4 (10 runs) · consistency 16.7

16-30 30%
other 20%
hedge 20%
refusal 30%

upstage/solar-pro-3 (10 runs) · consistency 8.3

31-45 10%
16-30 20%
0-15 30%
other 10%
hedge 10%
refusal 20%

xAI

x-ai/grok-4.7 (10 runs) · consistency 33.3

31-45 50%
16-30 20%
refusal 30%

x-ai/grok-4.5 (13 runs) · consistency 27.8

31-45 31%
16-30 31%
46-60 38%

x-ai/grok-4.3 (9 runs) · consistency 44.4

61-100 11%
other 22%
refusal 67%

x-ai/grok-4.20 (13 runs) · consistency 58.3

16-30 69%
0-15 15%
46-60 15%

Xiaomi

xiaomi/mimo-v2.5-pro (11 runs) · consistency 36.1

31-45 64%
16-30 27%

Z.ai

z-ai/glm-5.2 (6 runs)

31-45 33%
16-30 17%
46-60 17%
other 17%
refusal 17%

z-ai/glm-5.1 (13 runs) · consistency 16.7

31-45 31%
16-30 15%
46-60 15%
61-100 15%
other 23%

z-ai/glm-5-turbo (6 runs)

31-45 17%
46-60 17%
other 67%

z-ai/glm-5 (15 runs) · consistency 44.4

31-45 20%
16-30 27%
46-60 53%

z-ai/glm-4.7-flash (5 runs)

31-45 40%
refusal 60%

z-ai/glm-4.7 (1 runs)

other 100%