Pairwise benchmark snapshot · Aug 17, 2026noindex (thin pair)

Anthropic Claude Sonnet Latest vs Gemini 1.5 Pro benchmark

Name: Anthropic Claude Sonnet Latest vs Gemini 1.5 Pro AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Anthropic Claude Sonnet Latest (~anthropic) and Gemini 1.5 Pro (Google) using the latest snapshots we have as of Aug 17, 2026. Gemini 1.5 Pro wins on output price at $5/1M. Gemini 1.5 Pro has the larger context window (2M tokens). Every cell below is a dated snapshot from a named public source — we do not invent missing scores, and we do not run SWE-bench ourselves.

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~anthropic

Anthropic Claude Sonnet Latest

Auto-discovered from OpenRouter (~anthropic/claude-sonnet-latest). Preview until a second source matches.

$10/1M out

Google

Gemini 1.5 Pro

First million-token Gemini Pro. Baseline for 1.5 vs 2.5 vs 3.x Pro.

Elo 1,260$5/1M out

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Instant pairwise benchmark recalculation across 400+ LLMs

Model A

Model B

Quick vs:vs Claude Opus 4.5 vs Claude Opus 4.6 vs Claude Sonnet 4.5 vs Claude 3.7 Sonnet

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Anthropic Claude Sonnet Latest (0)vsGemini 1.5 Pro (9)

Anthropic Claude Sonnet Latest: 0W (0%)Overall: Gemini 1.5 ProGemini 1.5 Pro: 9W (100%)

← Anthropic Claude Sonnet LatestGemini 1.5 Pro →

Gemini 1.5 Pro (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

—vs1,260

Coding Elo

—vs—

SWE-bench

—vs38%

LiveBench

—vs49.2%

GPQA Diamond

—vs58%

Anthropic Claude Sonnet Latest: 0WGemini 1.5 Pro: 4W

Gemini 1.5 Pro (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs70 tok/s

Time to first token

—vs240 ms

Anthropic Claude Sonnet Latest: 0WGemini 1.5 Pro: 2W

Gemini 1.5 Pro (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$10/1Mvs$5/1M

Input price

$2/1Mvs$1.25/1M

Context window

1Mvs2M

Anthropic Claude Sonnet Latest: 0WGemini 1.5 Pro: 3W

Capability Matchup Radar

Multi-Dimensional Capability Radar

Each spoke is a skill. Farther from the center is better (0–100th percentile). Tap any dot to inspect details.

Tap any node to inspect

Percentile 0–100

Dimensional AdvantageGemini 1.5 Pro 6/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

Gemini 1.5 Pro

$5.00/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,260

LiveBench

High is better

—

LiveBenchHigh is better

49.2%

SWE-bench

High is better

—

SWE-benchHigh is better

38%

GPQA

High is better

—

GPQAHigh is better

58%

TTFT

Low is better

—

TTFTLow is better

240 ms

Speed

High is better

—

SpeedHigh is better

70 tok/s

In $

Low is better

$2.00 / 1M

In $Low is better

$1.25 / 1M+60%

Out $

Low is better

$10.00 / 1M

Out $Low is better

$5.00 / 1M+100%

Context

High is better

ContextHigh is better

2M+100%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

Simulate monthly production API costs in USD (US Dollar).

Save up to 46% with Gemini 1.5 Pro

Monthly Volume50M tokens/mo

Quick Presets:

Token Ratio (In vs Out)70% In / 30% Out

RAG / Search (10% out)Coding / Chat (50% out)

Anthropic Claude Sonnet Latest$220.00 / mo

In: $70Out: $150

Gemini 1.5 Pro$118.75 / mo

In: $43.75Out: $75

Estimated Cost Delta

Gemini 1.5 Pro is estimated to save $101.25/month ($1,215/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Gemini 1.5 Pro:Pick Gemini 1.5 Pro when you are optimizing output cost.
2
Gemini 1.5 Pro:Pick Gemini 1.5 Pro for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGemini 1.5 Pro

Lower output list price ($5/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGemini 1.5 Pro

Larger window (2M).

Screenshots / visionGemini 1.5 Pro

Gemini 1.5 Pro is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Gemini 1.5 Pro	Lower output list price ($5/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Gemini 1.5 Pro	Larger window (2M).
Screenshots / vision	Gemini 1.5 Pro	Gemini 1.5 Pro is the side marked multimodal in the catalog.

Community Sentiment

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CompareLLM Matrix

Verified head-to-head card

LIVE

~anthropic

Anthropic Claude Sonnet Latest

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$10/1M

Google

Gemini 1.5 Pro

Elo 1,260

LiveBench49.2%

SWE-bench38%

Speed70 tok/s

Output cost$5/1M

Frequently Asked Questions

Which is better overall, Anthropic Claude Sonnet Latest or Gemini 1.5 Pro?: We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.
Which is better at coding, Anthropic Claude Sonnet Latest or Gemini 1.5 Pro?: SWE-bench is missing for at least one model, so we do not rank coding from a single number.
Which is cheaper to run in production?: Gemini 1.5 Pro output tokens are $5/1M versus $10/1M. Input prices and retry rates still move the real bill.
Which is faster, Anthropic Claude Sonnet Latest or Gemini 1.5 Pro?: We do not have TTFT for both models.
Which has the larger context window?: Gemini 1.5 Pro accepts 2M tokens versus 1M.
Can I self-host either model?: Neither model is marked open-weights here. You are comparing hosted APIs.
Are these scores from CompareLLM’s own evals?: No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.
What does preference Elo mean on this page?: Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Anthropic Claude Sonnet Latest and Gemini 1.5 Pro Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Anthropic Claude Sonnet Latest matchups →|All Gemini 1.5 Pro matchups →

Gemini 1.5 Pro vs Gemini 2.5 Pro (next gemini-pro)Gemini 3 Pro vs Gemini 1.5 Pro Gemini 3 Flash vs Gemini 1.5 Pro Gemini 2.0 Flash Thinking vs Gemini 1.5 Pro Gemini 3.6 Pro vs Gemini 1.5 Pro Gemini 3.6 Flash vs Gemini 1.5 Pro

Anthropic Claude Sonnet Latest vs Gemini 1.5 Pro benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Anthropic Claude Sonnet Latest (0)vsGemini 1.5 Pro (9)

Anthropic Claude Sonnet Latest: 0W (0%)Overall: Gemini 1.5 ProGemini 1.5 Pro: 9W (100%)

← Anthropic Claude Sonnet LatestGemini 1.5 Pro →

Gemini 1.5 Pro (4/5)

Intelligence & Reasoning

Preference Elo, Coding proficiency, SWE-bench & LiveBench accuracy

Preference Elo

—vs1,260

Coding Elo

—vs—

SWE-bench

—vs38%

LiveBench

—vs49.2%

GPQA Diamond

—vs58%

Anthropic Claude Sonnet Latest: 0WGemini 1.5 Pro: 4W

Gemini 1.5 Pro (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs70 tok/s

Time to first token

—vs240 ms

Anthropic Claude Sonnet Latest: 0WGemini 1.5 Pro: 2W

Gemini 1.5 Pro (3/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$10/1Mvs$5/1M

Input price

$2/1Mvs$1.25/1M

Context window

1Mvs2M

Anthropic Claude Sonnet Latest: 0WGemini 1.5 Pro: 3W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatGemini 1.5 Pro

Lower output list price ($5/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGGemini 1.5 Pro

Larger window (2M).

Screenshots / visionGemini 1.5 Pro

Gemini 1.5 Pro is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	insufficient data	Need SWE-bench on both sides.
High-volume chat	Gemini 1.5 Pro	Lower output list price ($5/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Gemini 1.5 Pro	Larger window (2M).
Screenshots / vision	Gemini 1.5 Pro	Gemini 1.5 Pro is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Anthropic Claude Sonnet Latest or Gemini 1.5 Pro?

We do not have preference Elo for both models, so we do not declare an overall winner. Compare the metrics that exist.

Which is better at coding, Anthropic Claude Sonnet Latest or Gemini 1.5 Pro?

SWE-bench is missing for at least one model, so we do not rank coding from a single number.

Which is cheaper to run in production?

Gemini 1.5 Pro output tokens are $5/1M versus $10/1M. Input prices and retry rates still move the real bill.

Which is faster, Anthropic Claude Sonnet Latest or Gemini 1.5 Pro?

We do not have TTFT for both models.

Which has the larger context window?

Gemini 1.5 Pro accepts 2M tokens versus 1M.

Can I self-host either model?

Neither model is marked open-weights here. You are comparing hosted APIs.

Are these scores from CompareLLM’s own evals?

No. V1 aggregates public leaderboards (and optional first-party latency pings). Each cell names its source and date. Read /methodology.

What does preference Elo mean on this page?

Preference Elo is a crowd vote from LMArena / Arena. People see two hidden answers and pick the one they like more. The model that wins more often gets a higher Elo. That means people preferred it — not that it passed a school test. It is not SWE-bench, not accuracy, and not a number we invent. Anthropic Claude Sonnet Latest and Gemini 1.5 Pro Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.