Pairwise benchmark snapshot · Aug 16, 2026

OpenAI: o3 Mini vs Qwen 2.5 Coder 32B benchmark

Name: OpenAI: o3 Mini vs Qwen 2.5 Coder 32B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares OpenAI: o3 Mini (OpenAI) and Qwen 2.5 Coder 32B (Alibaba) using the latest snapshots we have as of Aug 16, 2026. On preference Elo, OpenAI: o3 Mini is ahead by 135 points (1,560 vs 1,425; seed-bootstrap (Aug 1, 2026)). On SWE-bench coding, OpenAI: o3 Mini resolves 78.5% versus 65.2% (seed-bootstrap (Aug 1, 2026)). Qwen 2.5 Coder 32B streams faster (110 tok/s) while Qwen 2.5 Coder 32B is the cheaper output token ($0.72/1M). OpenAI: o3 Mini 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: o3 Mini

Auto-discovered from OpenRouter (openai/o3-mini). Preview until a second source matches.

Elo 1,560$4.4/1M out

Alibaba

Qwen 2.5 Coder 32B

Alibaba dedicated open-weight code generation model with near-frontier SWE-bench Verified coding capability.

Elo 1,425$0.72/1M out

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Model A

Model B

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Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

OpenAI: o3 Mini (6)vsQwen 2.5 Coder 32B (4)

OpenAI: o3 Mini: 6W (60%)Overall: OpenAI: o3 MiniQwen 2.5 Coder 32B: 4W (40%)

← OpenAI: o3 MiniQwen 2.5 Coder 32B →

OpenAI: o3 Mini (5/5)

Intelligence & Reasoning

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

Preference Elo

1,560vs1,425

Coding Elo

1,585vs1,495

SWE-bench

78.5%vs65.2%

LiveBench

72.4%vs64.8%

GPQA Diamond

87.2%vs74%

OpenAI: o3 Mini: 5WQwen 2.5 Coder 32B: 0W

Qwen 2.5 Coder 32B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

92 tok/svs110 tok/s

Time to first token

290 msvs180 ms

OpenAI: o3 Mini: 0WQwen 2.5 Coder 32B: 2W

Qwen 2.5 Coder 32B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$4.4/1Mvs$0.72/1M

Input price

$1.1/1Mvs$0.18/1M

Context window

200kvs131k

OpenAI: o3 Mini: 1WQwen 2.5 Coder 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 AdvantageOpenAI: o3 Mini 4/6

Preference Elo

OpenAI: o3 Mini

135 pts advantage

Throughput Speed

Qwen 2.5 Coder 32B

18 tok/s faster

Price Efficiency

Qwen 2.5 Coder 32B

$3.68/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

+9%1,560

EloHigh is better

1,425

Code Elo

High is better

+6%1,585

Code EloHigh is better

1,495

LiveBench

High is better

+12%72.4%

LiveBenchHigh is better

64.8%

SWE-bench

High is better

+20%78.5%

SWE-benchHigh is better

65.2%

GPQA

High is better

+18%87.2%

GPQAHigh is better

74%

TTFT

Low is better

290 ms

TTFTLow is better

180 ms+61%

Speed

High is better

92 tok/s

SpeedHigh is better

110 tok/s+20%

In $

Low is better

$1.1/1M

In $Low is better

$0.18/1M+511%

Out $

Low is better

$4.4/1M

Out $Low is better

$0.72/1M+511%

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 84% with Qwen 2.5 Coder 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: o3 Mini$104.50 / mo

In: $38.50Out: $66.00

Qwen 2.5 Coder 32B$17.10 / mo

In: $6.30Out: $10.80

Estimated Cost Delta

Qwen 2.5 Coder 32B is estimated to save $87.40/month ($1,049/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
OpenAI: o3 Mini:Pick OpenAI: o3 Mini when repo-level coding accuracy is the constraint.
2
Qwen 2.5 Coder 32B:Pick Qwen 2.5 Coder 32B when you are optimizing output cost.
3
Qwen 2.5 Coder 32B:Pick Qwen 2.5 Coder 32B when time-to-first-token matters more than peak Elo.

Recommended Workload Routing

Repo / coding agentsOpenAI: o3 Mini

Higher SWE-bench (78.5%).

High-volume chatQwen 2.5 Coder 32B

Lower output list price ($0.72/1M).

Voice / low-latency UIQwen 2.5 Coder 32B

Lower TTFT (180 ms).

Long-document RAGOpenAI: o3 Mini

Larger window (200k).

Screenshots / visionOpenAI: o3 Mini

OpenAI: o3 Mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	OpenAI: o3 Mini	Higher SWE-bench (78.5%).
High-volume chat	Qwen 2.5 Coder 32B	Lower output list price ($0.72/1M).
Voice / low-latency UI	Qwen 2.5 Coder 32B	Lower TTFT (180 ms).
Long-document RAG	OpenAI: o3 Mini	Larger window (200k).
Screenshots / vision	OpenAI: o3 Mini	OpenAI: o3 Mini is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

OpenAI

OpenAI: o3 Mini

Elo 1,560

LiveBench72.4%

SWE-bench78.5%

Speed92 tok/s

Output cost$4.4/1M

Alibaba

Qwen 2.5 Coder 32B

Elo 1,425

LiveBench64.8%

SWE-bench65.2%

Speed110 tok/s

Output cost$0.72/1M

Frequently Asked Questions

Which is better overall, OpenAI: o3 Mini or Qwen 2.5 Coder 32B?: OpenAI: o3 Mini has the higher preference Elo in our latest snapshot (1,560). “Better” still depends on coding, price, and latency — see the table.
Which is better at coding, OpenAI: o3 Mini or Qwen 2.5 Coder 32B?: OpenAI: o3 Mini leads SWE-bench at 78.5% vs 65.2%. SWE-bench is one harness, not your repo.
Which is cheaper to run in production?: Qwen 2.5 Coder 32B output tokens are $0.72/1M versus $4.4/1M. Input prices and retry rates still move the real bill.
Which is faster, OpenAI: o3 Mini or Qwen 2.5 Coder 32B?: Qwen 2.5 Coder 32B has the lower time-to-first-token (180 ms vs 290 ms). Tokens/sec is a separate column if you care about long completions.
Which has the larger context window?: OpenAI: o3 Mini accepts 200k tokens versus 131k.
Can I self-host either model?: Qwen 2.5 Coder 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: o3 Mini and Qwen 2.5 Coder 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.

Similar Head-to-Head Comparisons

All OpenAI: o3 Mini matchups →|All Qwen 2.5 Coder 32B matchups →

OpenAI: o3 Mini vs OpenAI o1-mini (previous gpt-mini)OpenAI: o3 Mini vs GPT-5 mini (next gpt-mini)Qwen 2.5 Coder 32B vs Qwen 2.5 Plus (previous qwen)Qwen 2.5 Coder 32B vs Qwen3 235B (next qwen)GPT-5 vs OpenAI: o3 Mini GPT-5.6 Terra vs OpenAI: o3 Mini

OpenAI: o3 Mini vs Qwen 2.5 Coder 32B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

OpenAI: o3 Mini (6)vsQwen 2.5 Coder 32B (4)

OpenAI: o3 Mini: 6W (60%)Overall: OpenAI: o3 MiniQwen 2.5 Coder 32B: 4W (40%)

← OpenAI: o3 MiniQwen 2.5 Coder 32B →

OpenAI: o3 Mini (5/5)

Intelligence & Reasoning

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

Preference Elo

1,560vs1,425

Coding Elo

1,585vs1,495

SWE-bench

78.5%vs65.2%

LiveBench

72.4%vs64.8%

GPQA Diamond

87.2%vs74%

OpenAI: o3 Mini: 5WQwen 2.5 Coder 32B: 0W

Qwen 2.5 Coder 32B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

92 tok/svs110 tok/s

Time to first token

290 msvs180 ms

OpenAI: o3 Mini: 0WQwen 2.5 Coder 32B: 2W

Qwen 2.5 Coder 32B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$4.4/1Mvs$0.72/1M

Input price

$1.1/1Mvs$0.18/1M

Context window

200kvs131k

OpenAI: o3 Mini: 1WQwen 2.5 Coder 32B: 2W

Recommended Workload Routing

Repo / coding agentsOpenAI: o3 Mini

Higher SWE-bench (78.5%).

High-volume chatQwen 2.5 Coder 32B

Lower output list price ($0.72/1M).

Voice / low-latency UIQwen 2.5 Coder 32B

Lower TTFT (180 ms).

Long-document RAGOpenAI: o3 Mini

Larger window (200k).

Screenshots / visionOpenAI: o3 Mini

OpenAI: o3 Mini is the side marked multimodal in the catalog.

Target Workload	Recommended Pick	Evaluation Rationale
Repo / coding agents	OpenAI: o3 Mini	Higher SWE-bench (78.5%).
High-volume chat	Qwen 2.5 Coder 32B	Lower output list price ($0.72/1M).
Voice / low-latency UI	Qwen 2.5 Coder 32B	Lower TTFT (180 ms).
Long-document RAG	OpenAI: o3 Mini	Larger window (200k).
Screenshots / vision	OpenAI: o3 Mini	OpenAI: o3 Mini is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, OpenAI: o3 Mini or Qwen 2.5 Coder 32B?

OpenAI: o3 Mini has the higher preference Elo in our latest snapshot (1,560). “Better” still depends on coding, price, and latency — see the table.

Which is better at coding, OpenAI: o3 Mini or Qwen 2.5 Coder 32B?

OpenAI: o3 Mini leads SWE-bench at 78.5% vs 65.2%. SWE-bench is one harness, not your repo.

Which is cheaper to run in production?

Qwen 2.5 Coder 32B output tokens are $0.72/1M versus $4.4/1M. Input prices and retry rates still move the real bill.

Which is faster, OpenAI: o3 Mini or Qwen 2.5 Coder 32B?

Qwen 2.5 Coder 32B has the lower time-to-first-token (180 ms vs 290 ms). Tokens/sec is a separate column if you care about long completions.

Which has the larger context window?

OpenAI: o3 Mini accepts 200k tokens versus 131k.

Can I self-host either model?

Qwen 2.5 Coder 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: o3 Mini and Qwen 2.5 Coder 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.