Noometry

Model comparison

GPT-5.3 Chat vs Qwen3.5-Flash

GPT-5.3 Chat and Qwen3.5-Flash score almost the same on the Noometry Index (42.1 vs 42.3), so choose on price, context window or the category you care about most.

Last verified . 17 shared benchmarks.

GPT-5.3 Chat OpenAI

42.1

Rank #109 Confirmed

Qwen3.5-Flash Alibaba (Qwen)

42.3

Rank #105 Confirmed

Summary

  • They share 17 benchmarks with published results for both. GPT-5.3 Chat scores higher in 4 categories and Qwen3.5-Flash in 4 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in coding, where GPT-5.3 Chat leads 40.8 to 33.9.
  • Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
  • Qwen3.5-Flash accepts more context: 1M tokens versus 128K.

Side by side

GPT-5.3 ChatQwen3.5-Flash
ProviderOpenAIAlibaba (Qwen)
Noometry Index42.142.3
Released2026-03-032026-02-23
WeightsProprietaryProprietary
Context window128K1M
Max output16K66K
Input $ / M tokens$1.75$0.10
Output $ / M tokens$14$0.40
Results tracked1832

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Category by category

Coding GPT-5.3 Chat leads

GPT-5.3 Chat: 40.8 (#124), Qwen3.5-Flash: 33.9 (#234)

BenchmarkGPT-5.3 ChatQwen3.5-Flash
LMArena Coding14081412
LMArena WebDev—1243
ALE-Bench—221.8

Agentic & Tool Use Not comparable

GPT-5.3 Chat: —, Qwen3.5-Flash: —

BenchmarkGPT-5.3 ChatQwen3.5-Flash
Vending-Bench 2—462.69

Reasoning Qwen3.5-Flash leads

GPT-5.3 Chat: 27.3 (#105), Qwen3.5-Flash: 32.9 (#63)

BenchmarkGPT-5.3 ChatQwen3.5-Flash
LMArena Hard Prompts13991404
Chess Puzzles—21%
Mystery Game Puzzles—20%
DTBench—82.9%
LMCA—29.1%
Epoch Capabilities Index—143.98

Math Too close to call

GPT-5.3 Chat: 35.4 (#146), Qwen3.5-Flash: 36.3 (#117)

BenchmarkGPT-5.3 ChatQwen3.5-Flash
LMArena Math13891407
FrontierMath (Tiers 1-3)—18.2%
OTIS Mock AIME 2024-2025—84.4%
FrontierMath (Feb 2025 set)—6.2%
FrontierMath Tier 4 (v1)—0%

Knowledge Qwen3.5-Flash leads

GPT-5.3 Chat: 38.2 (#137), Qwen3.5-Flash: 43.2 (#84)

BenchmarkGPT-5.3 ChatQwen3.5-Flash
LMArena Expert13971408
GPQA Diamond—82.3%
SimpleQA Verified—20.3%
Vectara Hallucination Rate—10.5%

Multilingual Too close to call

GPT-5.3 Chat: 50.5 (#119), Qwen3.5-Flash: 50.7 (#116)

BenchmarkGPT-5.3 ChatQwen3.5-Flash
LMArena Non-English13831385
LMArena Chinese14331446
LMArena French13981412
LMArena German13841389
LMArena Japanese13511369
LMArena Korean13471344
LMArena Russian14001379
LMArena Spanish13711399

Instruction Following Too close to call

GPT-5.3 Chat: 73.0 (#124), Qwen3.5-Flash: 72.8 (#133)

BenchmarkGPT-5.3 ChatQwen3.5-Flash
LMArena Instruction Following13781374

Long Context Too close to call

GPT-5.3 Chat: 42.6 (#115), Qwen3.5-Flash: 42.4 (#119)

BenchmarkGPT-5.3 ChatQwen3.5-Flash
LMArena Longer Query13961392

Writing & Preference GPT-5.3 Chat leads

GPT-5.3 Chat: 63.3 (#65), Qwen3.5-Flash: 58.2 (#117)

BenchmarkGPT-5.3 ChatQwen3.5-Flash
LMArena Text13891397
LMArena Creative Writing13561343
LMArena Multi-Turn14131393
EQ-Bench Creative Writing1690—

Frequently asked questions

Is GPT-5.3 Chat better than Qwen3.5-Flash?

GPT-5.3 Chat and Qwen3.5-Flash score almost the same on the Noometry Index (42.1 vs 42.3), so choose on price, context window or the category you care about most.

Which is cheaper, GPT-5.3 Chat or Qwen3.5-Flash?

Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.

Is GPT-5.3 Chat or Qwen3.5-Flash better for coding?

GPT-5.3 Chat scores higher on coding benchmarks: 40.8 versus 33.9 in the Noometry coding category.

Which has the bigger context window?

Qwen3.5-Flash does, with 1M tokens against 128K.

How many benchmarks do GPT-5.3 Chat and Qwen3.5-Flash share?

17 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and Qwen3.5-Flash has 32.

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