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

Qwen: Qwen3.7 Max vs Yi-Large benchmark

Name: Qwen: Qwen3.7 Max vs Yi-Large AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

In this head-to-head showdown, 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.

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Executive Verdict Summary

Yi-Large holds empirical advantage (2 of 3 metrics)

Coding / SWESWE-bench

Yi-LargeTop code solve rate

ReasoningGPQA / Live

Yi-LargeTop logical accuracy

Best Value$/1M Tok

Yi-LargeLowest API billing cost

Speed / TokTok/Sec

Yi-LargeFastest stream rate

Verified Advantage Breakdown

3 benchmarks evaluated across capability, speed, and cost

Qwen: Qwen3.7 Max (1)Yi-Large (2)

Qwen: Qwen3.7 Max

1 of 3 Wins

✓Context window

Yi-Large

2 of 3 Wins

✓Input price✓Output price

Alibaba

Leads 1 of 3

Qwen: Qwen3.7 Max

Auto-discovered from OpenRouter (qwen/qwen3.7-max). Preview until a second source matches.

In: $1.475 · Out: $4.425/1M

01.AI

Leads 2 of 3

Yi-Large

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

Elo 1,430In: $0.3 · Out: $0.3/1M

Top Rival Showdowns for Qwen: Qwen3.7 Max

All Matchups

Compare vs:vs Claude Opus 4.5 vs GPT-5 vs Gemini 3 Pro vs Grok 4.6 vs DeepSeek V4 Pro

Preference Leader

No shared data

Single model data

Throughput Leader

No shared data

No latency data

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 standard models across 6 key capability dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect

0–100 %ile

Overall Matchup Breakdown

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

Qwen: Qwen3.7 Max (1)vsYi-Large (9)

Qwen: Qwen3.7 Max: 1W (10%)Yi-Large: 9W (90%)

← Qwen: Qwen3.7 MaxYi-Large →

🏆Yi-Large Leads(5/5)

Intelligence & Reasoning

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

Benchmark

Qwen: Qwen3.7 MaxvsYi-Large

Preference Elo

—vs1,430

Coding Elo

—vs1,410

SWE-bench

—vs53.8%

LiveBench

—vs60.5%

GPQA Diamond

—vs72.4%

Qwen: Qwen3.7 Max: 0WYi-Large: 5W

🏆Yi-Large Leads(2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Benchmark

Qwen: Qwen3.7 MaxvsYi-Large

Output speed

—vs90 tok/s

Time to first token

—vs220 ms

Qwen: Qwen3.7 Max: 0WYi-Large: 2W

🏆Yi-Large Leads(2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Benchmark

Qwen: Qwen3.7 MaxvsYi-Large

Output price

$4.425/1Mvs$0.3/1M+$4.125/1M

Input price

$1.475/1Mvs$0.3/1M+$1.175/1M

Context window

1Mvs33k+967k

Qwen: Qwen3.7 Max: 1WYi-Large: 2W

Side-by-Side Benchmark Matrix

Qwen: Qwen3.7 MaxYi-Large

Preference Elo

Qwen: Qwen3.7 Max—

Yi-Large1,430

Coding Elo

Qwen: Qwen3.7 Max—

Yi-Large1,410

LiveBench

Qwen: Qwen3.7 Max—

Yi-Large60.5%

SWE-bench

Qwen: Qwen3.7 Max—

Yi-Large53.8%

GPQA Diamond

Qwen: Qwen3.7 Max—

Yi-Large72.4%

Time to first token

Qwen: Qwen3.7 Max—

Yi-Large220 ms

Output speed

Qwen: Qwen3.7 Max—

Yi-Large90 tok/s

Input priceYi-Large +$1.175/1M

Qwen: Qwen3.7 Max$1.475/1M

Yi-Large$0.3/1M

Output priceYi-Large +$4.125/1M

Qwen: Qwen3.7 Max$4.425/1M

Yi-Large$0.3/1M

Context windowQwen: Qwen3.7 Max +967k

Qwen: Qwen3.7 Max1M

Yi-Large33k

Benchmark	Qwen: Qwen3.7 Max	Yi-Large	Advantage Delta
Preference Elo	—	1,430 lmarena · Aug 17, 2026	—
Coding Elo	—	1,410 lmarena · Aug 17, 2026	—
LiveBench	—	60.5% livebench · Aug 17, 2026	—
SWE-bench	—	53.8% swebench · Aug 17, 2026	—
GPQA Diamond	—	72.4% seed-bootstrap · Aug 1, 2026	—
Time to first token	—	220 ms seed-bootstrap · Aug 1, 2026	—
Output speed	—	90 tok/s seed-bootstrap · Aug 1, 2026	—
Input price	$1.475/1M openrouter · Aug 17, 2026	$0.3/1M seed-bootstrap · Aug 1, 2026	+$1.175/1M
Output price	$4.425/1M openrouter · Aug 17, 2026	$0.3/1M seed-bootstrap · Aug 1, 2026	+$4.125/1M
Context window	1M openrouter · Aug 17, 2026	33k seed-bootstrap · Aug 1, 2026	+967k

Workload Cost & Savings Calculator

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

Save 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)

Qwen: Qwen3.7 Max$118.00 / mo

In: $51.63Out: $66.38

Yi-Large$15.00 / mo

In: $10.5Out: $4.5

Estimated Cost Delta

Yi-Large is estimated to save $103.00/month ($1,236/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Yi-Large:Pick Yi-Large when you are optimizing output cost.
2
Qwen: Qwen3.7 Max:Pick Qwen: Qwen3.7 Max for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatYi-Large

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGQwen: Qwen3.7 Max

Larger window (1M).

Screenshots / visionYi-Large

Yi-Large 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	Yi-Large	Lower output list price ($0.3/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Qwen: Qwen3.7 Max	Larger window (1M).
Screenshots / vision	Yi-Large	Yi-Large is the side marked multimodal in the catalog.

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CompareLLM AI Matrix

Verified Head-to-Head Telemetry

LIVE BENCHMARK

Alibaba

Qwen: Qwen3.7 Max

Elo n/a

SWE-bench—

Speed (tok/s)1M

Input / 1M Tokens$1.475/1M

Output / 1M Tokens$4.425/1M

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, Qwen: Qwen3.7 Max or Yi-Large?: 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, Qwen: Qwen3.7 Max or Yi-Large?: 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?: Yi-Large output tokens are $0.3/1M versus $4.425/1M. Input prices and retry rates still move the real bill.
Which is faster, Qwen: Qwen3.7 Max or Yi-Large?: We do not have TTFT for both models.
Which has the larger context window?: Qwen: Qwen3.7 Max accepts 1M 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. Qwen: Qwen3.7 Max and Yi-Large Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Qwen: Qwen3.7 Max matchups →|All Yi-Large matchups →

Yi-Large vs Yi-Lightning (next other)Qwen 3 Max vs Yi-Large Qwen QwQ 32B vs Yi-Large Qwen 2.5 Plus vs Yi-Large Qwen2.5 Coder 32B Instruct vs Yi-Large Claude Opus 4.5 vs Yi-Large

Capability Percentiles

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

Multi-Dimensional Capability Radar

Leaders Matchup Capability Radar

Comparing top standard models across 6 key capability dimensions. Tap any spoke or dot to inspect.

Tap any node to inspect

0–100 %ile

Side-by-Side Benchmark Matrix

Qwen: Qwen3.7 MaxYi-Large

Preference Elo

Qwen: Qwen3.7 Max—

Yi-Large1,430

Coding Elo

Qwen: Qwen3.7 Max—

Yi-Large1,410

LiveBench

Qwen: Qwen3.7 Max—

Yi-Large60.5%

SWE-bench

Qwen: Qwen3.7 Max—

Yi-Large53.8%

GPQA Diamond

Qwen: Qwen3.7 Max—

Yi-Large72.4%

Time to first token

Qwen: Qwen3.7 Max—

Yi-Large220 ms

Output speed

Qwen: Qwen3.7 Max—

Yi-Large90 tok/s

Input priceYi-Large +$1.175/1M

Qwen: Qwen3.7 Max$1.475/1M

Yi-Large$0.3/1M

Output priceYi-Large +$4.125/1M

Qwen: Qwen3.7 Max$4.425/1M

Yi-Large$0.3/1M

Context windowQwen: Qwen3.7 Max +967k

Qwen: Qwen3.7 Max1M

Yi-Large33k

Benchmark

Qwen: Qwen3.7 Max

Yi-Large

Advantage Delta

Preference Elo

—

1,430

lmarena · Aug 17, 2026

—

Coding Elo

—

1,410

lmarena · Aug 17, 2026

—

LiveBench

—

60.5%

livebench · Aug 17, 2026

—

SWE-bench

—

53.8%

swebench · Aug 17, 2026

—

GPQA Diamond

—

72.4%

seed-bootstrap · Aug 1, 2026

—

Time to first token

—

220 ms

seed-bootstrap · Aug 1, 2026

—

Output speed

—

90 tok/s

seed-bootstrap · Aug 1, 2026

—

Input price

$1.475/1M

openrouter · Aug 17, 2026

$0.3/1M

seed-bootstrap · Aug 1, 2026

+$1.175/1M

Output price

$4.425/1M

openrouter · Aug 17, 2026

$0.3/1M

seed-bootstrap · Aug 1, 2026

+$4.125/1M

Context window

openrouter · Aug 17, 2026

33k

seed-bootstrap · Aug 1, 2026

+967k

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatYi-Large

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGQwen: Qwen3.7 Max

Larger window (1M).

Screenshots / visionYi-Large

Yi-Large 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	Yi-Large	Lower output list price ($0.3/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Qwen: Qwen3.7 Max	Larger window (1M).
Screenshots / vision	Yi-Large	Yi-Large is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Qwen: Qwen3.7 Max or Yi-Large?

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, Qwen: Qwen3.7 Max or Yi-Large?

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?

Yi-Large output tokens are $0.3/1M versus $4.425/1M. Input prices and retry rates still move the real bill.

Which is faster, Qwen: Qwen3.7 Max or Yi-Large?

We do not have TTFT for both models.

Which has the larger context window?

Qwen: Qwen3.7 Max accepts 1M 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. Qwen: Qwen3.7 Max and Yi-Large Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.