CompareLLM
CompareLLM.ai
Live
Leaderboard
Models
Compare
Best of & Stacks
Research & News
…
CompareLLM
CompareLLM.ai
Precision Benchmarks

Programmatic, dated AI model benchmarks, head-to-head comparisons, and Stack Engine presets.

Daily ingest · 06:00 UTC

Analytics & Benchmarks

  • AI Model Leaderboard
  • Head-to-Head Compare Hub
  • Models Directory
  • Stack Engine Presets
  • Frontier Models
  • Open Weights Catalog

Guides & Intent Lists

  • Best LLM Lists (2026)
  • Best Coding LLM
  • Best Cheap LLM
  • Fastest Low-Latency LLM
  • Claude vs GPT Benchmark
  • What is Elo?
  • Methodology Guides
  • News & Dispatches

Transparency & API

  • Evaluation Methodology
  • Benchmark Changelog
  • Public JSON API
  • llms.txt Specification
  • Privacy Policy
  • Sign In / Account

© 2026 CompareLLM. Public benchmark data aggregated from Arena Elo, LiveBench, SWE-bench & OpenRouter.

Every score has a dated snapshot.

Theme:
Currency:
  1. Home
  2. Comparisons
  3. Gemini 1.5 Pro vs Yi-Large

Pairwise benchmark snapshot · Aug 1, 2026

Gemini 1.5 Pro vs Yi-Large benchmark

In this head-to-head showdown, Yi-Large delivers higher overall intelligence and human-preferred responses (Elo 1,430 vs 1,260), while Yi-Large leads in SWE-bench software engineering benchmarks (53.8%), while Yi-Large is more budget-friendly at $0.3/1M per 1M output tokens. Review the complete breakdown below to determine which model best fits your performance and budget requirements.

Executive Comparison Verdict

Bottom Line: Yi-Large holds the advantage over Gemini 1.5 Pro in overall benchmark performance and human evaluation rankings. Choose Yi-Large for demanding workloads, or review the breakdown below to compare coding and pricing metrics.
Share Analysis:
WhatsAppTelegramXLinkedInReddit

Verified Head-to-Head Advantage Breakdown

9 direct benchmark disciplines evaluated across capability, speed, and cost

Gemini 1.5 Pro (1)Yi-Large (8)
Gemini 1.5 Pro
1 of 9 Wins
✓Context window
Yi-Large
8 of 9 Wins
✓Preference Elo✓LiveBench✓SWE-bench✓GPQA Diamond✓Time to first token✓Output speed✓Input price✓Output price
Google
Leads 1 of 9 metrics
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
01.AI
Leads 8 of 9 metrics
Yi-Large

01.AI full-scale dense model for complex instruction following.

Elo 1,430$0.3/1M out
Top Rival Showdowns for Gemini 1.5 Pro
All Matchups
Compare vs:vs Claude Opus 4.5vs GPT-5vs Grok 4.6vs DeepSeek V4 Provs Qwen 3 Max
Preference LeaderYi-Large Wins

Yi-Large

Δ 170 Arena Elo pts

Throughput LeaderYi-Large Wins

Yi-Large

90 tok/s

Value per Dollar LeaderYi-Large Wins

Yi-Large

$0.3 / 1M output

Capability Percentiles

Relative percentile scores computed across all active models in the benchmark catalog.

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top Western standard models with China's leading frontier rival across 6 skill dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect
0–100 %ile
Head-to-Head Comparison

Overall Matchup Breakdown

Category wins across reasoning intelligence, generation speed, and token cost.

Gemini 1.5 Pro (1)vsYi-Large (9)
Gemini 1.5 Pro: 1W (10%)Overall: Yi-LargeYi-Large: 9W (90%)
← Gemini 1.5 ProYi-Large →
🏆Yi-Large(5/5)

Intelligence & Reasoning

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

Benchmark
Gemini 1.5 ProvsYi-Large
Preference Elo
1,260vs1,430+170
Coding Elo
—vs1,410
SWE-bench
38%vs53.8%+15.8%
LiveBench
49.2%vs60.5%+11.3%
GPQA Diamond
58%vs72.4%+14.4%
Gemini 1.5 Pro: 0WYi-Large: 5W
🏆Yi-Large(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark
Gemini 1.5 ProvsYi-Large
Output speed
70 tok/svs90 tok/s+20 tok/s
Time to first token
240 msvs220 ms+20 ms
Gemini 1.5 Pro: 0WYi-Large: 2W
🏆Yi-Large(2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark
Gemini 1.5 ProvsYi-Large
Output price
$5/1Mvs$0.3/1M+$4.7/1M
Input price
$1.25/1Mvs$0.3/1M+$0.95/1M
Context window
2Mvs33k+2M
Gemini 1.5 Pro: 1WYi-Large: 2W

Side-by-Side Benchmark Matrix

Preference Elo+170
Gemini 1.5 Pro1,260
seed-bootstrap · Aug 1, 2026
Yi-Large1,430
seed-bootstrap · Aug 1, 2026
Coding Elo
Gemini 1.5 Pro—
Yi-Large1,410
seed-bootstrap · Aug 1, 2026
LiveBench+11.3%
Gemini 1.5 Pro49.2%
seed-bootstrap · Aug 1, 2026
Yi-Large60.5%
seed-bootstrap · Aug 1, 2026
SWE-bench+15.8%
Gemini 1.5 Pro38%
seed-bootstrap · Aug 1, 2026
Yi-Large53.8%
seed-bootstrap · Aug 1, 2026
GPQA Diamond+14.4%
Gemini 1.5 Pro58%
seed-bootstrap · Aug 1, 2026
Yi-Large72.4%
seed-bootstrap · Aug 1, 2026
Time to first token+20 ms
Gemini 1.5 Pro240 ms
seed-bootstrap · Aug 1, 2026
Yi-Large220 ms
seed-bootstrap · Aug 1, 2026
Output speed+20 tok/s
Gemini 1.5 Pro70 tok/s
seed-bootstrap · Aug 1, 2026
Yi-Large90 tok/s
seed-bootstrap · Aug 1, 2026
Input price+$0.95/1M
Gemini 1.5 Pro$1.25/1M
seed-bootstrap · Aug 1, 2026
Yi-Large$0.3/1M
seed-bootstrap · Aug 1, 2026
Output price+$4.7/1M
Gemini 1.5 Pro$5/1M
seed-bootstrap · Aug 1, 2026
Yi-Large$0.3/1M
seed-bootstrap · Aug 1, 2026
Context window+2M
Gemini 1.5 Pro2M
seed-bootstrap · Aug 1, 2026
Yi-Large33k
seed-bootstrap · Aug 1, 2026
BenchmarkGemini 1.5 ProYi-LargeAdvantage Delta
Preference Elo
1,260
seed-bootstrap · Aug 1, 2026
1,430
seed-bootstrap · Aug 1, 2026
+170
Coding Elo—
1,410
seed-bootstrap · Aug 1, 2026
—
LiveBench
49.2%
seed-bootstrap · Aug 1, 2026
60.5%
seed-bootstrap · Aug 1, 2026
+11.3%
SWE-bench
38%
seed-bootstrap · Aug 1, 2026
53.8%
seed-bootstrap · Aug 1, 2026
+15.8%
GPQA Diamond
58%
seed-bootstrap · Aug 1, 2026
72.4%
seed-bootstrap · Aug 1, 2026
+14.4%
Time to first token
240 ms
seed-bootstrap · Aug 1, 2026
220 ms
seed-bootstrap · Aug 1, 2026
+20 ms
Output speed
70 tok/s
seed-bootstrap · Aug 1, 2026
90 tok/s
seed-bootstrap · Aug 1, 2026
+20 tok/s
Input price
$1.25/1M
seed-bootstrap · Aug 1, 2026
$0.3/1M
seed-bootstrap · Aug 1, 2026
+$0.95/1M
Output price
$5/1M
seed-bootstrap · Aug 1, 2026
$0.3/1M
seed-bootstrap · Aug 1, 2026
+$4.7/1M
Context window
2M
seed-bootstrap · Aug 1, 2026
33k
seed-bootstrap · Aug 1, 2026
+2M
Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 87% with Yi-Large
Monthly Volume50M tokens/mo
Quick Presets:
Token Ratio (In vs Out)70% In / 30% Out
RAG / Search (10% out)Coding / Chat (50% out)
Gemini 1.5 Pro$118.75 / mo
In: $43.75Out: $75
Yi-Large$15.00 / mo
In: $10.5Out: $4.5
Estimated Cost Delta

Yi-Large is estimated to save $103.75/month ($1,245/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

  • 1
    Yi-Large:Pick Yi-Large when repo-level coding accuracy is the constraint.
  • 2
    Yi-Large:Pick Yi-Large when time-to-first-token matters more than peak Elo.
  • 3
    Gemini 1.5 Pro:Pick Gemini 1.5 Pro for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsYi-Large

Higher SWE-bench (53.8%).

High-volume chatYi-Large

Lower output list price ($0.3/1M).

Voice / low-latency UIYi-Large

Lower TTFT (220 ms).

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 WorkloadRecommended PickEvaluation Rationale
Repo / coding agentsYi-LargeHigher SWE-bench (53.8%).
High-volume chatYi-LargeLower output list price ($0.3/1M).
Voice / low-latency UIYi-LargeLower TTFT (220 ms).
Long-document RAGGemini 1.5 ProLarger window (2M).
Screenshots / visionGemini 1.5 ProGemini 1.5 Pro is the side marked multimodal in the catalog.
Community Sentiment

Cast Your Matchup Vote

0 total votes

Community Discussions (0)

Sign in to cast your verified vote, bookmark models, and participate in benchmark discussions.Sign In to Post

No comments posted on this matchup yet. Be the first to share an evaluation note!

Social Share Card Preview

Dynamic OpenGraph banner generated at /compare/gemini-1-5-pro-vs-yi-large/opengraph-image

Save PNG

CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK
VS
Google

Gemini 1.5 Pro

Elo 1,260
SWE-bench38%
Speed (tok/s)70 tok/s
Input / 1M Tokens$1.25/1M
Output / 1M Tokens$5/1M
01.AI

Yi-Large

Elo 1,430
SWE-bench53.8%
Speed (tok/s)90 tok/s
Input / 1M Tokens$0.3/1M
Output / 1M Tokens$0.3/1M

Frequently Asked Questions

Which is better overall, Gemini 1.5 Pro or Yi-Large?
Yi-Large has the higher preference Elo in our latest snapshot (1,430). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Gemini 1.5 Pro or Yi-Large?
Yi-Large leads SWE-bench at 53.8% vs 38%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?
Yi-Large output tokens are $0.3/1M versus $5/1M. Input prices and retry rates still move the real bill.
Which is faster, Gemini 1.5 Pro or Yi-Large?
Yi-Large has the lower time-to-first-token (220 ms vs 240 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?
Gemini 1.5 Pro accepts 2M tokens versus 33k.
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. Gemini 1.5 Pro and Yi-Large Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Gemini 1.5 Pro matchups →|All Yi-Large matchups →
Gemini 1.5 Pro vs Gemini 2.5 Pro (next gemini-pro)Yi-Large vs Yi-Lightning (next other)Gemini 3 Pro vs Yi-LargeGemini 3 Flash vs Yi-LargeGemini 2.0 Flash Thinking vs Yi-LargeGemini 3.6 Pro vs Yi-Large