Pairwise benchmark snapshot · Aug 16, 2026noindex (thin pair)

OpenAI: GPT-5.6 Terra (batch) vs Qwen QwQ 32B benchmark

Name: OpenAI: GPT-5.6 Terra (batch) vs Qwen QwQ 32B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares OpenAI: GPT-5.6 Terra (batch) (OpenAI) and Qwen QwQ 32B (Alibaba) using the latest snapshots we have as of Aug 16, 2026. Qwen QwQ 32B wins on output price at $1.2/1M. OpenAI: GPT-5.6 Terra (batch) has the larger context window (1.1M 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: GPT-5.6 Terra (batch)

Auto-discovered from OpenRouter (openai/gpt-5.6-terra:batch). Preview until a second source matches.

$6/1M 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: GPT-5.6 Terra (batch) (1)vsQwen QwQ 32B (9)

OpenAI: GPT-5.6 Terra (batch): 1W (10%)Overall: Qwen QwQ 32BQwen QwQ 32B: 9W (90%)

← OpenAI: GPT-5.6 Terra (batch)Qwen 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%

OpenAI: GPT-5.6 Terra (batch): 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

OpenAI: GPT-5.6 Terra (batch): 0WQwen QwQ 32B: 2W

Qwen QwQ 32B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$6/1Mvs$1.2/1M

Input price

$1/1Mvs$0.3/1M

Context window

1.1Mvs131k

OpenAI: GPT-5.6 Terra (batch): 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

No shared data

Throughput Speed

No shared data

Price Efficiency

Qwen QwQ 32B

$4.80/1M 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

$1/1M

In $Low is better

$0.3/1M+233%

Out $

Low is better

$6/1M

Out $Low is better

$1.2/1M+400%

Context

High is better

+701%1.1M

ContextHigh is better

131k

Interactive Simulator

Workload Cost & Savings Calculator

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

Save up to 77% 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: GPT-5.6 Terra (batch)$125.00 / mo

In: $35.00Out: $90.00

Qwen QwQ 32B$28.50 / mo

In: $10.50Out: $18.00

Estimated Cost Delta

Qwen QwQ 32B is estimated to save $96.50/month ($1,158/year).

Based on 50M tokens (30% gen)

Key Selection Recommendations

1
Qwen QwQ 32B:Pick Qwen QwQ 32B when you are optimizing output cost.
2
OpenAI: GPT-5.6 Terra (batch):Pick OpenAI: GPT-5.6 Terra (batch) for million-token RAG or long-document jobs.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatQwen QwQ 32B

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.6 Terra (batch)

Larger window (1.1M).

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	Qwen QwQ 32B	Lower output list price ($1.2/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.6 Terra (batch)	Larger window (1.1M).
Screenshots / vision	Qwen QwQ 32B	Qwen QwQ 32B is the side marked multimodal in the catalog.

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CompareLLM Matrix

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LIVE

OpenAI

OpenAI: GPT-5.6 Terra (batch)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$6/1M

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: GPT-5.6 Terra (batch) 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, OpenAI: GPT-5.6 Terra (batch) 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?: Qwen QwQ 32B output tokens are $1.2/1M versus $6/1M. Input prices and retry rates still move the real bill.
Which is faster, OpenAI: GPT-5.6 Terra (batch) or Qwen QwQ 32B?: We do not have TTFT for both models.
Which has the larger context window?: OpenAI: GPT-5.6 Terra (batch) accepts 1.1M 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: GPT-5.6 Terra (batch) 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: GPT-5.6 Terra (batch) matchups →|All Qwen QwQ 32B matchups →

Qwen QwQ 32B vs Qwen3 235B (previous qwen)Qwen QwQ 32B vs Qwen 3 Max (next qwen)GPT-5 vs Qwen QwQ 32B GPT-4.5 Orion vs Qwen QwQ 32B GPT-5.6 Sol vs Qwen QwQ 32B GPT-5.6 Terra vs Qwen QwQ 32B

OpenAI: GPT-5.6 Terra (batch) vs Qwen QwQ 32B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

OpenAI: GPT-5.6 Terra (batch) (1)vsQwen QwQ 32B (9)

OpenAI: GPT-5.6 Terra (batch): 1W (10%)Overall: Qwen QwQ 32BQwen QwQ 32B: 9W (90%)

← OpenAI: GPT-5.6 Terra (batch)Qwen 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%

OpenAI: GPT-5.6 Terra (batch): 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

OpenAI: GPT-5.6 Terra (batch): 0WQwen QwQ 32B: 2W

Qwen QwQ 32B (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$6/1Mvs$1.2/1M

Input price

$1/1Mvs$0.3/1M

Context window

1.1Mvs131k

OpenAI: GPT-5.6 Terra (batch): 1WQwen QwQ 32B: 2W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatQwen QwQ 32B

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

Voice / low-latency UIinsufficient data

Need TTFT on both sides.

Long-document RAGOpenAI: GPT-5.6 Terra (batch)

Larger window (1.1M).

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	Qwen QwQ 32B	Lower output list price ($1.2/1M).
Voice / low-latency UI	insufficient data	Need TTFT on both sides.
Long-document RAG	OpenAI: GPT-5.6 Terra (batch)	Larger window (1.1M).
Screenshots / vision	Qwen QwQ 32B	Qwen QwQ 32B is the side marked multimodal in the catalog.

Frequently Asked Questions

Which is better overall, OpenAI: GPT-5.6 Terra (batch) 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, OpenAI: GPT-5.6 Terra (batch) 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?

Qwen QwQ 32B output tokens are $1.2/1M versus $6/1M. Input prices and retry rates still move the real bill.

Which is faster, OpenAI: GPT-5.6 Terra (batch) or Qwen QwQ 32B?

We do not have TTFT for both models.

Which has the larger context window?

OpenAI: GPT-5.6 Terra (batch) accepts 1.1M 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: GPT-5.6 Terra (batch) and Qwen QwQ 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.