Noometry

Model comparison

GPT-5.3 Chat vs Qwen3 14B

GPT-5.3 Chat is the stronger model overall, scoring 42.1 to 35.0 on the Noometry Index. Qwen3 14B costs 7.9× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.

Last verified . 0 shared benchmarks.

GPT-5.3 Chat OpenAI

42.1

Rank #109 Confirmed

Qwen3 14B Alibaba (Qwen)

35.0

Rank #222 Confirmed

Summary

  • The widest gap is in reasoning, where GPT-5.3 Chat leads 27.3 to 18.1.
  • Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Chat.
  • Qwen3 14B accepts more context: 131K tokens versus 128K.
  • Qwen3 14B has downloadable open weights; the other is API-only.

Side by side

GPT-5.3 ChatQwen3 14B
ProviderOpenAIAlibaba (Qwen)
Noometry Index42.135.0
Released2026-03-032025-04
WeightsProprietaryOpen
Context window128K131K
Max output16K8K
Input $ / M tokens$1.75$0.35
Output $ / M tokens$14$1.40
Results tracked1812

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Category by category

Coding GPT-5.3 Chat leads

GPT-5.3 Chat: 40.8 (#124), Qwen3 14B: 36.7 (#191)

BenchmarkGPT-5.3 ChatQwen3 14B
SciCode—31.6%
LMArena Coding1408—

Agentic & Tool Use Not comparable

GPT-5.3 Chat: —, Qwen3 14B: 29.4 (#78)

BenchmarkGPT-5.3 ChatQwen3 14B
Berkeley Function Calling Leaderboard—41%

Reasoning GPT-5.3 Chat leads

GPT-5.3 Chat: 27.3 (#105), Qwen3 14B: 18.1 (#272)

BenchmarkGPT-5.3 ChatQwen3 14B
Kagi LLM Benchmark—49.1%
CritPt—0%
Chess Puzzles—4%
LMArena Hard Prompts1399—
DTBench—64%
LMCA—18.2%
Epoch Capabilities Index—138.23

Math Qwen3 14B leads

GPT-5.3 Chat: 35.4 (#146), Qwen3 14B: 37.0 (#102)

BenchmarkGPT-5.3 ChatQwen3 14B
OTIS Mock AIME 2024-2025—66.4%
LMArena Math1389—

Knowledge Qwen3 14B leads

GPT-5.3 Chat: 38.2 (#137), Qwen3 14B: 39.2 (#124)

BenchmarkGPT-5.3 ChatQwen3 14B
GPQA Diamond—63.8%
Vectara Hallucination Rate—5.4%
LMArena Expert1397—

Multilingual Not comparable

GPT-5.3 Chat: 50.5 (#119), Qwen3 14B: —

BenchmarkGPT-5.3 ChatQwen3 14B
LMArena Non-English1383—
LMArena Chinese1433—
LMArena French1398—
LMArena German1384—
LMArena Japanese1351—
LMArena Korean1347—
LMArena Russian1400—
LMArena Spanish1371—

Instruction Following Not comparable

GPT-5.3 Chat: 73.0 (#124), Qwen3 14B: —

BenchmarkGPT-5.3 ChatQwen3 14B
LMArena Instruction Following1378—

Long Context GPT-5.3 Chat leads

GPT-5.3 Chat: 42.6 (#115), Qwen3 14B: 38.0 (#201)

BenchmarkGPT-5.3 ChatQwen3 14B
Fiction.LiveBench—62.5%
LMArena Longer Query1396—

Writing & Preference Not comparable

GPT-5.3 Chat: 63.3 (#65), Qwen3 14B: —

BenchmarkGPT-5.3 ChatQwen3 14B
LMArena Text1389—
LMArena Creative Writing1356—
EQ-Bench Creative Writing1690—
LMArena Multi-Turn1413—

Frequently asked questions

Is GPT-5.3 Chat better than Qwen3 14B?

GPT-5.3 Chat is the stronger model overall, scoring 42.1 to 35.0 on the Noometry Index. Qwen3 14B costs 7.9× less per token, which makes it the better buy when GPT-5.3 Chat's lead doesn't matter for your workload.

Which is cheaper, GPT-5.3 Chat or Qwen3 14B?

Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; GPT-5.3 Chat lists at $1.75 and $14.

Is GPT-5.3 Chat or Qwen3 14B better for coding?

GPT-5.3 Chat scores higher on coding benchmarks: 40.8 versus 36.7 in the Noometry coding category.

Which has the bigger context window?

Qwen3 14B does, with 131K tokens against 128K.

How many benchmarks do GPT-5.3 Chat and Qwen3 14B share?

0 benchmarks have published results for both models. GPT-5.3 Chat has 18 scored results on Noometry and Qwen3 14B has 12.

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