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

NVIDIA: Nemotron Nano 9B V2 (free) vs Qwen QwQ 32B benchmark

Name: NVIDIA: Nemotron Nano 9B V2 (free) vs Qwen QwQ 32B AI benchmark comparison
Creator: CompareLLM
License: https://creativecommons.org/licenses/by/4.0/

This page compares NVIDIA: Nemotron Nano 9B V2 (free) (nvidia) and Qwen QwQ 32B (Alibaba) using the latest snapshots we have as of Aug 16, 2026. NVIDIA: Nemotron Nano 9B V2 (free) wins on output price at $0/1M. 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.

Share Analysis:

WhatsApp Telegram X / Post LinkedIn Reddit

nvidia

NVIDIA: Nemotron Nano 9B V2 (free)

Auto-discovered from OpenRouter (nvidia/nemotron-nano-9b-v2:free). Preview until a second source matches.

$0/1M out

Alibaba

Qwen QwQ 32B

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

Elo 1,495$1.2/1M out

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.

NVIDIA: Nemotron Nano 9B V2 (free) (2)vsQwen QwQ 32B (8)

NVIDIA: Nemotron Nano 9B V2 (free): 2W (20%)Overall: Qwen QwQ 32BQwen QwQ 32B: 8W (80%)

← NVIDIA: Nemotron Nano 9B V2 (free)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%

NVIDIA: Nemotron Nano 9B V2 (free): 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

NVIDIA: Nemotron Nano 9B V2 (free): 0WQwen QwQ 32B: 2W

NVIDIA: Nemotron Nano 9B V2 (free) (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0/1Mvs$1.2/1M

Input price

$0/1Mvs$0.3/1M

Context window

128kvs131k

NVIDIA: Nemotron Nano 9B V2 (free): 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

Price Efficiency

NVIDIA: Nemotron Nano 9B V2 (free)

$1.20/1M 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

$0/1M

In $Low is better

$0.3/1M

Out $

Low is better

$0/1M

Out $Low is better

$1.2/1M

Context

High is better

128k

ContextHigh is better

131k+2%

Key Selection Recommendations

1
NVIDIA: Nemotron Nano 9B V2 (free):Pick NVIDIA: Nemotron Nano 9B V2 (free) when you are optimizing output cost.

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatNVIDIA: Nemotron Nano 9B V2 (free)

Lower output list price ($0/1M).

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	NVIDIA: Nemotron Nano 9B V2 (free)	Lower output list price ($0/1M).
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.

Community Sentiment

Cast Your Matchup Vote

0 total votes

Community Discussions (0)

No comments posted on this matchup yet. Be the first to share an evaluation note!

Share card

The real PNG is generated at /compare/nemotron-nano-9b-v2-free-vs-qwq-32b/opengraph-image for crawlers.

PNG

CompareLLM Matrix

Verified head-to-head card

LIVE

nvidia

NVIDIA: Nemotron Nano 9B V2 (free)

Elo n/a

LiveBench—

SWE-bench—

Speed—

Output cost$0/1M

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, NVIDIA: Nemotron Nano 9B V2 (free) 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, NVIDIA: Nemotron Nano 9B V2 (free) 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?: NVIDIA: Nemotron Nano 9B V2 (free) output tokens are $0/1M versus $1.2/1M. Input prices and retry rates still move the real bill.
Which is faster, NVIDIA: Nemotron Nano 9B V2 (free) 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 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. NVIDIA: Nemotron Nano 9B V2 (free) 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 NVIDIA: Nemotron Nano 9B V2 (free) matchups →|All Qwen QwQ 32B matchups →

Qwen QwQ 32B vs Qwen3 235B (previous qwen)Qwen QwQ 32B vs Qwen 3 Max (next qwen)Qwen 2.5 Plus vs Qwen QwQ 32B Qwen3.8 27B vs Qwen QwQ 32B Qwen 2.5 Coder 32B vs Qwen QwQ 32B Claude Opus 4.5 vs Qwen QwQ 32B

NVIDIA: Nemotron Nano 9B V2 (free) vs Qwen QwQ 32B benchmark

Interactive Comparison Diagram

Matchup Breakdown

Tug-of-War Matchup Matrix

Category wins across intelligence, speed, and pricing efficiency.

NVIDIA: Nemotron Nano 9B V2 (free) (2)vsQwen QwQ 32B (8)

NVIDIA: Nemotron Nano 9B V2 (free): 2W (20%)Overall: Qwen QwQ 32BQwen QwQ 32B: 8W (80%)

← NVIDIA: Nemotron Nano 9B V2 (free)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%

NVIDIA: Nemotron Nano 9B V2 (free): 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

NVIDIA: Nemotron Nano 9B V2 (free): 0WQwen QwQ 32B: 2W

NVIDIA: Nemotron Nano 9B V2 (free) (2/3)

Pricing & Capacity

Cost per million tokens and max context window length

Output price

$0/1Mvs$1.2/1M

Input price

$0/1Mvs$0.3/1M

Context window

128kvs131k

NVIDIA: Nemotron Nano 9B V2 (free): 2WQwen QwQ 32B: 1W

Recommended Workload Routing

Repo / coding agentsinsufficient data

Need SWE-bench on both sides.

High-volume chatNVIDIA: Nemotron Nano 9B V2 (free)

Lower output list price ($0/1M).

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	NVIDIA: Nemotron Nano 9B V2 (free)	Lower output list price ($0/1M).
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, NVIDIA: Nemotron Nano 9B V2 (free) 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, NVIDIA: Nemotron Nano 9B V2 (free) 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?

NVIDIA: Nemotron Nano 9B V2 (free) output tokens are $0/1M versus $1.2/1M. Input prices and retry rates still move the real bill.

Which is faster, NVIDIA: Nemotron Nano 9B V2 (free) 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 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. NVIDIA: Nemotron Nano 9B V2 (free) and Qwen QwQ 32B Elo cells are dated snapshots from the named source — we do not compute Arena ourselves.