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Gemini 1.0 Pro 002Mistral Large 4 OSS


Vals IndexGDP-weighted benchmark	N/A	56.42%±1.26
Legal Research BenchAgentic US legal research	N/A	35.58%±3.33
Finance Agent v2.1Core financial analyst tasks	N/A	61.72%±2.05
Tax Agent BenchAgentic US corporate tax research	N/A	27.33%±2.95
Terminal-Bench 4.0Frontier-difficulty terminal tasks	N/A	26.26%±5.13
Vibe Code Bench v1.1Building web apps from scratch	N/A	81.56%±3.29

Benchmarks

Vals Index *

Gemini 1.0 Pro 002

N/A

Mistral Large 4 OSS

0.00%± 1.26

(30/30)

Legal Research Bench *

Gemini 1.0 Pro 002

N/A

Mistral Large 4 OSS

0.00%± 3.33

(88/88)

Finance Agent v2.1 *

Gemini 1.0 Pro 002

N/A

Mistral Large 4 OSS

0.00%± 2.05

(34/34)

Tax Agent Bench *

Gemini 1.0 Pro 002

N/A

Mistral Large 4 OSS

0.00%± 2.95

(79/79)

Terminal-Bench 4.0

Gemini 1.0 Pro 002

N/A

Mistral Large 4 OSS

0.00%± 5.13

(58/58)

Vibe Code Bench v1.1 *

Gemini 1.0 Pro 002

N/A

Mistral Large 4 OSS

0.00%± 3.29

(122/122)

Overall performance

Performance on the Vals Index, a GDP-weighted aggregation of tasks across finance, coding, and law

•2026-10-29

Gemini 1.0 Pro 002 Mistral Large 4 OSS

Comparison by Industry

Model performance on different sections of the economy.

Legal

70.25%

vs.

25.70%

Finance

N/A

vs.

52.58%

Coding

N/A

vs.

53.91%

Cost Analysis

Per task and per token model pricing.

Vals Index · USD

N/A

$3.717

Cost / TestVals Index

N/A

vs.

$3.717

Input Cost/ 1M Tokens

$0.50

vs.

$0.70

Input Cache Read/ 1M Tokens

$0.125

vs.

$0.07

Output Cost/ 1M Tokens

$1.50

vs.

$2.10

Model Metadata

Basic information about each model.


Model provider	Google	Mistral AI
Latency	N/A	2868.04s
Cost (In/Out)	$0.5 / $1.5	$0.7 / $2.1
Context Window	33k	1M
Max Output Token	8k	256k
Input Modality