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

AllenAI: Olmo 3 32B Think vs Qwen QwQ 32B benchmark

Name: AllenAI: Olmo 3 32B Think vs Qwen QwQ 32B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares AllenAI: Olmo 3 32B Think (allenai) and Qwen QwQ 32B (Alibaba) using the latest snapshots we have as of Aug 17, 2026. AllenAI: Olmo 3 32B Think wins on output price at $0.5/1M. 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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allenai

AllenAI: Olmo 3 32B Think

Auto-discovered from OpenRouter (allenai/olmo-3-32b-think). Preview until a second source matches.

$0.5/1M out

Alibaba

Qwen QwQ 32B

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

QwQ ReasoningElo 1,495$1.2/1M out

Qwen QwQ 32B Inference Compute Profile

Inference-Time Compute & Reasoning EffortDynamic CoT

Qwen QwQ 32B Reasoning Scaler & Token Billing Simulator

Param: enable_reasoning

Reasoning models scale test-time compute by generating hidden chain-of-thought (CoT) tokens. These tokens are billed at standard output rates and directly expand latency (TTFT) in exchange for higher GPQA Diamond and SWE-bench Verified problem resolve rates.

Estimated TTFT

960 ms

3x latency

CoT Thinking Tokens

~7,200

Billed as output tokens

Est. Cost / 1k Calls

$9.15

17.9x base invoice

STEM / SWE Boost

+11.8%

GPQA & SWE-bench scaling

High (Max QwQ CoT) Operational Profile

Exhaustive exploration of problem constraints and self-verification.

Direct Provider APIAlibaba

"enable_reasoning": true

OpenRouter Unified APIUnified Gateway

"reasoning": {
  "effort": "high",
  "max_tokens": 7200
}

Swap or Add Any Model to this Matchup

Instant pairwise benchmark recalculation across 400+ LLMs

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.

AllenAI: Olmo 3 32B Think (2)vsQwen QwQ 32B (8)

AllenAI: Olmo 3 32B Think: 2W (20%)Overall: Qwen QwQ 32BQwen QwQ 32B: 8W (80%)

← AllenAI: Olmo 3 32B ThinkQwen QwQ 32B →

Qwen QwQ 32B (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,495

Coding Elo

—vs1,520

SWE-bench

—vs67.5%

LiveBench

—vs68%

GPQA Diamond

—vs83.2%

AllenAI: Olmo 3 32B Think: 0WQwen QwQ 32B: 5W

Qwen QwQ 32B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs68 tok/s

Time to first token

—vs320 ms

AllenAI: Olmo 3 32B Think: 0WQwen QwQ 32B: 2W

AllenAI: Olmo 3 32B Think (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.5/1Mvs$1.2/1M

Input price

$0.15/1Mvs$0.3/1M

Context window

66kvs131k

AllenAI: Olmo 3 32B Think: 2WQwen 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 5/6

Preference Elo

No shared data

Throughput Speed

No shared data

Token Price Efficiency

AllenAI: Olmo 3 32B Think

$0.70/1M cheaper

Full Benchmark Score Matrix

—

Elo

High is better

—

EloHigh is better

1,495

Code Elo

High is better

—

Code EloHigh is better

1,520

LiveBench

High is better

—

LiveBenchHigh is better

68%

SWE-bench

High is better

—

SWE-benchHigh is better

67.5%

GPQA

High is better

—

GPQAHigh is better

83.2%

TTFT

Low is better

—

TTFTLow is better

320 ms

Speed

High is better

—

SpeedHigh is better

68 tok/s

In $

Low is better

+100%$0.15 / 1M

In $Low is better

$0.30 / 1M

Out $

Low is better

+140%$0.50 / 1M

Out $Low is better

$1.20 / 1M

Context

High is better

66k

ContextHigh is better

131k+100%

Interactive Simulator (USD)

Workload Cost & Savings Calculator

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

Save up to 55% with AllenAI: Olmo 3 32B Think

Monthly Volume50M tokens/mo

Quick Presets:

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

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

AllenAI: Olmo 3 32B Think$12.75 / mo

In: $5.25Out: $7.5

Qwen QwQ 32B$28.50 / mo

In: $10.5Out: $18

Estimated Cost Delta

AllenAI: Olmo 3 32B Think is estimated to save $15.75/month ($189/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
AllenAI: Olmo 3 32B Think:Pick AllenAI: Olmo 3 32B Think when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatAllenAI: Olmo 3 32B Think

Lower output list price ($0.5/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGQwen QwQ 32B

Larger window (131k).

Screenshots / visionQwen QwQ 32B

Qwen QwQ 32B 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	AllenAI: Olmo 3 32B Think	Lower output list price ($0.5/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Qwen QwQ 32B	Larger window (131k).
Screenshots / vision	Qwen QwQ 32B	Qwen QwQ 32B is the side marked multimodal in the catalog.

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LIVE

allenai

AllenAI: Olmo 3 32B Think

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0.5/1M

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, AllenAI: Olmo 3 32B Think or Qwen QwQ 32B?: 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, AllenAI: Olmo 3 32B Think or Qwen QwQ 32B?: 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?: AllenAI: Olmo 3 32B Think output tokens are $0.5/1M versus $1.2/1M. Input prices and retry rates still move the real bill.
Which is faster, AllenAI: Olmo 3 32B Think or Qwen QwQ 32B?: We do not have TTFT for both models.
Which has the larger context window?: Qwen QwQ 32B accepts 131k tokens versus 66k.
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. AllenAI: Olmo 3 32B Think 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 AllenAI: Olmo 3 32B Think matchups →|All Qwen QwQ 32B matchups →

Qwen QwQ 32B vs Qwen3 235B (previous qwen)Qwen 3 Max vs Qwen QwQ 32B Qwen 2.5 Plus vs Qwen QwQ 32B Qwen3.8 27B vs Qwen QwQ 32B Qwen 2.5 Coder 32B vs Qwen QwQ 32B Qwen2.5 Coder 32B Instruct vs Qwen QwQ 32B

AllenAI: Olmo 3 32B Think vs Qwen QwQ 32B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

AllenAI: Olmo 3 32B Think (2)vsQwen QwQ 32B (8)

AllenAI: Olmo 3 32B Think: 2W (20%)Overall: Qwen QwQ 32BQwen QwQ 32B: 8W (80%)

← AllenAI: Olmo 3 32B ThinkQwen QwQ 32B →

Qwen QwQ 32B (5/5)

Intelligence & Reasoning

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

Preference Elo

—vs1,495

Coding Elo

—vs1,520

SWE-bench

—vs67.5%

LiveBench

—vs68%

GPQA Diamond

—vs83.2%

AllenAI: Olmo 3 32B Think: 0WQwen QwQ 32B: 5W

Qwen QwQ 32B (2/2)

Speed & Latency

Generation throughput and time to first token responsiveness

Output speed

—vs68 tok/s

Time to first token

—vs320 ms

AllenAI: Olmo 3 32B Think: 0WQwen QwQ 32B: 2W

AllenAI: Olmo 3 32B Think (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0.5/1Mvs$1.2/1M

Input price

$0.15/1Mvs$0.3/1M

Context window

66kvs131k

AllenAI: Olmo 3 32B Think: 2WQwen QwQ 32B: 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatAllenAI: Olmo 3 32B Think

Lower output list price ($0.5/1M).

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGQwen QwQ 32B

Larger window (131k).

Screenshots / visionQwen QwQ 32B

Qwen QwQ 32B 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	AllenAI: Olmo 3 32B Think	Lower output list price ($0.5/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	Qwen QwQ 32B	Larger window (131k).
Screenshots / vision	Qwen QwQ 32B	Qwen QwQ 32B is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, AllenAI: Olmo 3 32B Think or Qwen QwQ 32B?

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, AllenAI: Olmo 3 32B Think or Qwen QwQ 32B?

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?

AllenAI: Olmo 3 32B Think output tokens are $0.5/1M versus $1.2/1M. Input prices and retry rates still move the real bill.

Which is faster, AllenAI: Olmo 3 32B Think or Qwen QwQ 32B?

We do not have TTFT for both models.

Which has the larger context window?

Qwen QwQ 32B accepts 131k tokens versus 66k.

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. AllenAI: Olmo 3 32B Think and Qwen QwQ 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.