Pairwise benchmark snapshot · Aug 1, 2026

Ernie 4.5 Turbo vs Qwen QwQ 32B benchmark

Name: Ernie 4.5 Turbo vs Qwen QwQ 32B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares Ernie 4.5 Turbo (Baidu) and Qwen QwQ 32B (Alibaba) using the latest snapshots we have as of Aug 1, 2026. On preference Elo, Qwen QwQ 32B is ahead by 45 points (1,495 vs 1,450; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Qwen QwQ 32B resolves 67.5% versus 57% (seed-bootstrap (Aug 1, 2026)). Ernie 4.5 Turbo streams faster (95 tok/s) while Ernie 4.5 Turbo is the cheaper output token ($1.2/1M). Qwen QwQ 32B has the larger context window (131k 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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Baidu

Ernie 4.5 Turbo

Baidu current multimodal enterprise foundation model with broad Chinese knowledge.

Elo 1,450$1.2/1M out

Alibaba

Qwen QwQ 32B

Alibaba specialized open reasoning model competing with frontier closed reasoning models.

Elo 1,495$1.2/1M out

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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.

Ernie 4.5 Turbo (2)vsQwen QwQ 32B (6)

Ernie 4.5 Turbo: 2W (25%)Overall: Qwen QwQ 32BQwen QwQ 32B: 6W (75%)

← Ernie 4.5 Turbo2 tiesQwen QwQ 32B →

Qwen QwQ 32B (5/5)

Intelligence & Reasoning

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

Preference Elo

1,450vs1,495

Coding Elo

1,435vs1,520

SWE-bench

57%vs67.5%

LiveBench

61%vs68%

GPQA Diamond

74.5%vs83.2%

Ernie 4.5 Turbo: 0WQwen QwQ 32B: 5W

Ernie 4.5 Turbo (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

95 tok/svs68 tok/s

Time to first token

200 msvs320 ms

Ernie 4.5 Turbo: 2WQwen QwQ 32B: 0W

Qwen QwQ 32B (1/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.2/1Mvs$1.2/1M

Input price

$0.3/1Mvs$0.3/1M

Context window

128kvs131k

Ernie 4.5 Turbo: 0WQwen QwQ 32B: 1W

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 AdvantageQwen QwQ 32B 4/6

Preference Elo

Qwen QwQ 32B

45 pts advantage

Throughput Speed

Ernie 4.5 Turbo

27 tok/s faster

Price Efficiency

Ernie 4.5 Turbo

Same token price

Full Benchmark Score Matrix

—

Elo

High is better

1,450

EloHigh is better

1,495+3%

Code Elo

High is better

1,435

Code EloHigh is better

1,520+6%

LiveBench

High is better

61%

LiveBenchHigh is better

68%+11%

SWE-bench

High is better

57%

SWE-benchHigh is better

67.5%+18%

GPQA

High is better

74.5%

GPQAHigh is better

83.2%+12%

TTFT

Low is better

+60%200 ms

TTFTLow is better

320 ms

Speed

High is better

+40%95 tok/s

SpeedHigh is better

68 tok/s

In $

Low is better

$0.3/1M

In $Low is better

$0.3/1M

Out $

Low is better

$1.2/1M

Out $Low is better

$1.2/1M

Context

High is better

128k

ContextHigh is better

131k+2%

Interactive Simulator

Workload Cost & Savings Calculator

Simulate monthly production API costs based on published $/1M tokens.

Monthly Volume50M tokens/mo

Quick Presets:

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

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

Ernie 4.5 Turbo$28.50 / mo

In: $10.50Out: $18.00

Qwen QwQ 32B$28.50 / mo

In: $10.50Out: $18.00

Key Selection Recommendations

1
Qwen QwQ 32B:Pick Qwen QwQ 32B when repo-level coding accuracy is the constraint.
2
Ernie 4.5 Turbo:Pick Ernie 4.5 Turbo when you are optimizing output cost.
3
Ernie 4.5 Turbo:Pick Ernie 4.5 Turbo when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsQwen QwQ 32B

Higher SWE-bench (67.5%).

High-volume chatErnie 4.5 Turbo

Lower output list price ($1.2/1M).

Voice / low-latency UIErnie 4.5 Turbo

Lower TTFT (200 ms).

Long-document RAGQwen QwQ 32B

Larger window (131k).

Screenshots / visionErnie 4.5 Turbo

Ernie 4.5 Turbo is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Qwen QwQ 32B	Higher SWE-bench (67.5%).
High-volume chat	Ernie 4.5 Turbo	Lower output list price ($1.2/1M).
Voice / low-latency UI	Ernie 4.5 Turbo	Lower TTFT (200 ms).
Long-document RAG	Qwen QwQ 32B	Larger window (131k).
Screenshots / vision	Ernie 4.5 Turbo	Ernie 4.5 Turbo is the side marked multimodal in the catalog.

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LIVE

Baidu

Ernie 4.5 Turbo

Elo 1,450

LiveBench61%

SWE-bench57%

Speed95 tok/s

Output cost$1.2/1M

Alibaba

Qwen QwQ 32B

Elo 1,495

LiveBench68%

SWE-bench67.5%

Speed68 tok/s

Output cost$1.2/1M

Frequently Asked Questions

Which is better overall, Ernie 4.5 Turbo or Qwen QwQ 32B?: Qwen QwQ 32B has the higher preference Elo in our latest snapshot (1,495). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, Ernie 4.5 Turbo or Qwen QwQ 32B?: Qwen QwQ 32B leads SWE-bench at 67.5% vs 57%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Ernie 4.5 Turbo output tokens are $1.2/1M versus $1.2/1M. Input prices and retry rates still move the real bill.
Which is faster, Ernie 4.5 Turbo or Qwen QwQ 32B?: Ernie 4.5 Turbo has the lower time-to-first-token (200 ms vs 320 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: Qwen QwQ 32B accepts 131k tokens versus 128k.
Can I self-host either model?: Qwen QwQ 32B is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.
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. Ernie 4.5 Turbo and Qwen QwQ 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All Ernie 4.5 Turbo matchups →|All Qwen QwQ 32B matchups →

Ernie 4.5 Turbo vs Yi-Lightning (previous other)Qwen QwQ 32B vs Qwen3 235B (previous qwen)Qwen QwQ 32B vs Qwen 3 Max (next qwen)Qwen 2.5 Plus vs Ernie 4.5 Turbo Qwen3 235B vs Ernie 4.5 Turbo Qwen 2.5 Coder 32B vs Ernie 4.5 Turbo

Ernie 4.5 Turbo vs Qwen QwQ 32B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

Ernie 4.5 Turbo (2)vsQwen QwQ 32B (6)

Ernie 4.5 Turbo: 2W (25%)Overall: Qwen QwQ 32BQwen QwQ 32B: 6W (75%)

← Ernie 4.5 Turbo2 tiesQwen QwQ 32B →

Qwen QwQ 32B (5/5)

Intelligence & Reasoning

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

Preference Elo

1,450vs1,495

Coding Elo

1,435vs1,520

SWE-bench

57%vs67.5%

LiveBench

61%vs68%

GPQA Diamond

74.5%vs83.2%

Ernie 4.5 Turbo: 0WQwen QwQ 32B: 5W

Ernie 4.5 Turbo (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

95 tok/svs68 tok/s

Time to first token

200 msvs320 ms

Ernie 4.5 Turbo: 2WQwen QwQ 32B: 0W

Qwen QwQ 32B (1/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$1.2/1Mvs$1.2/1M

Input price

$0.3/1Mvs$0.3/1M

Context window

128kvs131k

Ernie 4.5 Turbo: 0WQwen QwQ 32B: 1W

Recommended Workload Routing

Repo / coding agentsQwen QwQ 32B

Higher SWE-bench (67.5%).

High-volume chatErnie 4.5 Turbo

Lower output list price ($1.2/1M).

Voice / low-latency UIErnie 4.5 Turbo

Lower TTFT (200 ms).

Long-document RAGQwen QwQ 32B

Larger window (131k).

Screenshots / visionErnie 4.5 Turbo

Ernie 4.5 Turbo is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	Qwen QwQ 32B	Higher SWE-bench (67.5%).
High-volume chat	Ernie 4.5 Turbo	Lower output list price ($1.2/1M).
Voice / low-latency UI	Ernie 4.5 Turbo	Lower TTFT (200 ms).
Long-document RAG	Qwen QwQ 32B	Larger window (131k).
Screenshots / vision	Ernie 4.5 Turbo	Ernie 4.5 Turbo is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, Ernie 4.5 Turbo or Qwen QwQ 32B?

Qwen QwQ 32B has the higher preference Elo in our latest snapshot (1,495). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, Ernie 4.5 Turbo or Qwen QwQ 32B?

Qwen QwQ 32B leads SWE-bench at 67.5% vs 57%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Ernie 4.5 Turbo output tokens are $1.2/1M versus $1.2/1M. Input prices and retry rates still move the real bill.

Which is faster, Ernie 4.5 Turbo or Qwen QwQ 32B?

Ernie 4.5 Turbo has the lower time-to-first-token (200 ms vs 320 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

Qwen QwQ 32B accepts 131k tokens versus 128k.

Can I self-host either model?

Qwen QwQ 32B is marked open-weights in our catalog. The other side is a closed API. Check the provider license before you ship weights.

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. Ernie 4.5 Turbo and Qwen QwQ 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.