Pairwise benchmark snapshot · Aug 16, 2026

OpenAI: o1 vs Qwen QwQ 32B benchmark

Name: OpenAI: o1 vs Qwen QwQ 32B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares OpenAI: o1 (OpenAI) and Qwen QwQ 32B (Alibaba) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, OpenAI: o1 is ahead by 17 points (1,512 vs 1,495; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, Qwen QwQ 32B resolves 67.5% versus 48.9% (seed-bootstrap (Aug 1, 2026)). Qwen QwQ 32B streams faster (68 tok/s) while Qwen QwQ 32B is the cheaper output token ($1.2/1M). OpenAI: o1 has the larger context window (200k 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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OpenAI

OpenAI: o1

Auto-discovered from OpenRouter (openai/o1). Preview until a second source matches.

Elo 1,512$60/1M 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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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.

OpenAI: o1 (2)vsQwen QwQ 32B (8)

OpenAI: o1: 2W (20%)Overall: Qwen QwQ 32BQwen QwQ 32B: 8W (80%)

← OpenAI: o1Qwen QwQ 32B →

Qwen QwQ 32B (4/5)

Intelligence & Reasoning

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

Preference Elo

1,512vs1,495

Coding Elo

1,485vs1,520

SWE-bench

48.9%vs67.5%

LiveBench

65.4%vs68%

GPQA Diamond

78%vs83.2%

OpenAI: o1: 1WQwen QwQ 32B: 4W

Qwen QwQ 32B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

45 tok/svs68 tok/s

Time to first token

420 msvs320 ms

OpenAI: o1: 0WQwen QwQ 32B: 2W

Qwen QwQ 32B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$60/1Mvs$1.2/1M

Input price

$15/1Mvs$0.3/1M

Context window

200kvs131k

OpenAI: o1: 1WQwen QwQ 32B: 2W

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 5/6

Preference Elo

OpenAI: o1

17 pts advantage

Throughput Speed

Qwen QwQ 32B

23 tok/s faster

Price Efficiency

Qwen QwQ 32B

$58.80/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+1%1,512

EloHigh is better

1,495

Code Elo

High is better

1,485

Code EloHigh is better

1,520+2%

LiveBench

High is better

65.4%

LiveBenchHigh is better

68%+4%

SWE-bench

High is better

48.9%

SWE-benchHigh is better

67.5%+38%

GPQA

High is better

78%

GPQAHigh is better

83.2%+7%

TTFT

Low is better

420 ms

TTFTLow is better

320 ms+31%

Speed

High is better

45 tok/s

SpeedHigh is better

68 tok/s+51%

In $

Low is better

$15/1M

In $Low is better

$0.3/1M+4900%

Out $

Low is better

$60/1M

Out $Low is better

$1.2/1M+4900%

Context

High is better

+53%200k

ContextHigh is better

131k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 98% with Qwen QwQ 32B

Monthly Volume50M tokens/mo

Quick Presets:

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

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

OpenAI: o1$1,425.00 / mo

In: $525.00Out: $900.00

Qwen QwQ 32B$28.50 / mo

In: $10.50Out: $18.00

Estimated Cost Delta

Qwen QwQ 32B is estimated to save $1,396.50/month ($16,758/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Qwen QwQ 32B:Pick Qwen QwQ 32B when repo-level coding accuracy is the constraint.
2
Qwen QwQ 32B:Pick Qwen QwQ 32B when time-to-first-token matters more than peak Elo.
3
OpenAI: o1:Pick OpenAI: o1 as the default general assistant.

Recommended Workload Routing

Repo / coding agentsQwen QwQ 32B

Higher SWE-bench (67.5%).

High-volume chatQwen QwQ 32B

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

Voice / low-latency UIQwen QwQ 32B

Lower TTFT (320 ms).

Long-document RAGOpenAI: o1

Larger window (200k).

Screenshots / visionOpenAI: o1

OpenAI: o1 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	Qwen QwQ 32B	Lower output list price ($1.2/1M).
Voice / low-latency UI	Qwen QwQ 32B	Lower TTFT (320 ms).
Long-document RAG	OpenAI: o1	Larger window (200k).
Screenshots / vision	OpenAI: o1	OpenAI: o1 is the side marked multimodal in the catalog.

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LIVE

OpenAI

OpenAI: o1

Elo 1,512

LiveBench65.4%

SWE-bench48.9%

Speed45 tok/s

Output cost$60/1M

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, OpenAI: o1 or Qwen QwQ 32B?: OpenAI: o1 has the higher preference Elo in our latest snapshot (1,512). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, OpenAI: o1 or Qwen QwQ 32B?: Qwen QwQ 32B leads SWE-bench at 67.5% vs 48.9%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Qwen QwQ 32B output tokens are $1.2/1M versus $60/1M. Input prices and retry rates still move the real bill.
Which is faster, OpenAI: o1 or Qwen QwQ 32B?: Qwen QwQ 32B has the lower time-to-first-token (320 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: OpenAI: o1 accepts 200k tokens versus 131k.
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. OpenAI: o1 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 OpenAI: o1 matchups →|All Qwen QwQ 32B matchups →

OpenAI: o1 vs GPT-4o (previous gpt-flagship)OpenAI: o1 vs GPT-4.5 Orion (next gpt-flagship)Qwen QwQ 32B vs Qwen3 235B (previous qwen)Qwen QwQ 32B vs Qwen 3 Max (next qwen)Qwen 3 Max vs OpenAI: o1 GPT-5.6 Terra vs OpenAI: o1

OpenAI: o1 vs Qwen QwQ 32B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

OpenAI: o1 (2)vsQwen QwQ 32B (8)

OpenAI: o1: 2W (20%)Overall: Qwen QwQ 32BQwen QwQ 32B: 8W (80%)

← OpenAI: o1Qwen QwQ 32B →

Qwen QwQ 32B (4/5)

Intelligence & Reasoning

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

Preference Elo

1,512vs1,495

Coding Elo

1,485vs1,520

SWE-bench

48.9%vs67.5%

LiveBench

65.4%vs68%

GPQA Diamond

78%vs83.2%

OpenAI: o1: 1WQwen QwQ 32B: 4W

Qwen QwQ 32B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

45 tok/svs68 tok/s

Time to first token

420 msvs320 ms

OpenAI: o1: 0WQwen QwQ 32B: 2W

Qwen QwQ 32B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$60/1Mvs$1.2/1M

Input price

$15/1Mvs$0.3/1M

Context window

200kvs131k

OpenAI: o1: 1WQwen QwQ 32B: 2W

Recommended Workload Routing

Repo / coding agentsQwen QwQ 32B

Higher SWE-bench (67.5%).

High-volume chatQwen QwQ 32B

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

Voice / low-latency UIQwen QwQ 32B

Lower TTFT (320 ms).

Long-document RAGOpenAI: o1

Larger window (200k).

Screenshots / visionOpenAI: o1

OpenAI: o1 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	Qwen QwQ 32B	Lower output list price ($1.2/1M).
Voice / low-latency UI	Qwen QwQ 32B	Lower TTFT (320 ms).
Long-document RAG	OpenAI: o1	Larger window (200k).
Screenshots / vision	OpenAI: o1	OpenAI: o1 is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, OpenAI: o1 or Qwen QwQ 32B?

OpenAI: o1 has the higher preference Elo in our latest snapshot (1,512). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, OpenAI: o1 or Qwen QwQ 32B?

Qwen QwQ 32B leads SWE-bench at 67.5% vs 48.9%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Qwen QwQ 32B output tokens are $1.2/1M versus $60/1M. Input prices and retry rates still move the real bill.

Which is faster, OpenAI: o1 or Qwen QwQ 32B?

Qwen QwQ 32B has the lower time-to-first-token (320 ms vs 420 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

OpenAI: o1 accepts 200k tokens versus 131k.

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. OpenAI: o1 and Qwen QwQ 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.