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GPT-5.2-Codex vs Qwen3.5 Plus 2026-04-20

GPT-5.2-Codex leads Qwen3.5 Plus 2026-04-20 on coding, 45.4 to 39.5 on the Vibe Coding Index, and Qwen3.5 Plus 2026-04-20 costs 7.8x less per output token ($1.80 vs $14.00 per million). Updated October 22, 2026; 4 benchmarks have a result for both.

GPT-5.2-CodexOpenAI
Coding
45.4
Overall
No data
Output $/M
$14.00
4
Qwen3.5 Plus 2026-04-20Qwen
Coding
39.5
Overall
No data
Output $/M
$1.80
0
vs boards won of 4 shared

GPT-5.2-Codex or Qwen3.5 Plus 2026-04-20: which to pick

Pick GPT-5.2-Codex for coding: it scores 45.4 on the Vibe Coding Index against 39.5 for Qwen3.5 Plus 2026-04-20.

Pick Qwen3.5 Plus 2026-04-20 for output tokens 7.8x cheaper ($1.80 vs $14.00 per million) and a larger context window (1M against 400K tokens).

Shared results
4
GPT-5.2-Codex only
18
Qwen3.5 Plus 2026-04-20 only
21
Like-for-like categories
1 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
GPT-5.2-Codex 45.4 from 3 benchmarks, Qwen3.5 Plus 2026-04-20 39.5 from 2 benchmarks.
Widest category
Coding, 12.3 points apart on average over 4 shared benchmarks.
Widest single gap
ALE-Bench: GPT-5.2-Codex 1299.9 against Qwen3.5 Plus 2026-04-20 608.9, 23.0 points apart on a 0 to 100 scale.
Output price
GPT-5.2-Codex $14.00 against Qwen3.5 Plus 2026-04-20 $1.80 per million output tokens, 7.8x apart.
Context window
GPT-5.2-Codex takes 400K tokens, Qwen3.5 Plus 2026-04-20 1M.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGPT-5.2-CodexBarsQwen3.5 Plus 2026-04-20Ties
Coding40
All shared boards40
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for GPT-5.2-Codex and Qwen3.5 Plus 2026-04-20
BenchmarkGPT-5.2-CodexQwen3.5 Plus 2026-04-20Leader
SWE-bench Verified72.8%Not measuredOnly GPT-5.2-Codex measured
SWE-bench Multilingual66.3%Not measuredOnly GPT-5.2-Codex measured
LMArena WebDev1339Not measuredOnly GPT-5.2-Codex measured
LiveCodeBench (Vals AI)88.0%85.3%GPT-5.2-Codex
SWE-bench Verified (Vals AI)72.4%71.2%GPT-5.2-Codex
Vibe Code Bench (Vals AI)37.9%15.7%GPT-5.2-Codex
Terminal-Bench Hard (Artificial Analysis run)37.1%Not measuredOnly GPT-5.2-Codex measured
Terminal-Bench66.5%Not measuredOnly GPT-5.2-Codex measured
ALE-Bench1299.9608.9GPT-5.2-Codex
LMArena WebDev: React1329Not measuredOnly GPT-5.2-Codex measured
LMArena WebDev: HTML1348Not measuredOnly GPT-5.2-Codex measured
Neither model has a result on the other 28 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for GPT-5.2-Codex and Qwen3.5 Plus 2026-04-20
BenchmarkGPT-5.2-CodexQwen3.5 Plus 2026-04-20Leader
AA Intelligence Index28.5Not measuredOnly GPT-5.2-Codex measured
Epoch Capabilities IndexNot measured146.2Only Qwen3.5 Plus 2026-04-20 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Agentic work benchmarks for GPT-5.2-Codex and Qwen3.5 Plus 2026-04-20
BenchmarkGPT-5.2-CodexQwen3.5 Plus 2026-04-20Leader
Design Arena: agents building web apps1051Not measuredOnly GPT-5.2-Codex measured
Design Arena: agents building full-stack apps993Not measuredOnly GPT-5.2-Codex measured
Design Arena: agents building mobile apps1090Not measuredOnly GPT-5.2-Codex measured
Design Arena: agents building Android apps1176Not measuredOnly GPT-5.2-Codex measured
Design Arena: agents building Godot games1142Not measuredOnly GPT-5.2-Codex measured
τ²-Bench Telecom92.1%Not measuredOnly GPT-5.2-Codex measured
Vending-Bench 2Not measured$1Only Qwen3.5 Plus 2026-04-20 measured
Neither model has a result on the other 34 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Reasoning benchmarks for GPT-5.2-Codex and Qwen3.5 Plus 2026-04-20
BenchmarkGPT-5.2-CodexQwen3.5 Plus 2026-04-20Leader
GPQA DiamondNot measured87.4%Only Qwen3.5 Plus 2026-04-20 measured
MMMU Pro (Vals AI)Not measured22.8%Only Qwen3.5 Plus 2026-04-20 measured
GPQA Diamond (Artificial Analysis run)89.9%Not measuredOnly GPT-5.2-Codex measured
Humanity's Last Exam (Artificial Analysis run)35.7%Not measuredOnly GPT-5.2-Codex measured
GPQA Diamond (Epoch AI run)Not measured84.8%Only Qwen3.5 Plus 2026-04-20 measured
Chess puzzlesNot measured8.0%Only Qwen3.5 Plus 2026-04-20 measured
Mystery game puzzlesNot measured17.0%Only Qwen3.5 Plus 2026-04-20 measured
Neither model has a result on the other 15 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Math benchmarks for GPT-5.2-Codex and Qwen3.5 Plus 2026-04-20
BenchmarkGPT-5.2-CodexQwen3.5 Plus 2026-04-20Leader
AIMENot measured86.0%Only Qwen3.5 Plus 2026-04-20 measured
OTIS Mock AIMENot measured86.7%Only Qwen3.5 Plus 2026-04-20 measured
Neither model has a result on the other 11 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Knowledge benchmarks for GPT-5.2-Codex and Qwen3.5 Plus 2026-04-20
BenchmarkGPT-5.2-CodexQwen3.5 Plus 2026-04-20Leader
MMLU ProNot measured87.2%Only Qwen3.5 Plus 2026-04-20 measured
LegalBench (Vals AI)Not measured85.1%Only Qwen3.5 Plus 2026-04-20 measured
CaseLaw (Vals AI)Not measured59.7%Only Qwen3.5 Plus 2026-04-20 measured
CorpFin (Vals AI)Not measured65.3%Only Qwen3.5 Plus 2026-04-20 measured
MortgageTax (Vals AI)Not measured60.8%Only Qwen3.5 Plus 2026-04-20 measured
MedQA (Vals AI)Not measured95.2%Only Qwen3.5 Plus 2026-04-20 measured
SimpleQA VerifiedNot measured25.4%Only Qwen3.5 Plus 2026-04-20 measured
Neither model has a result on the other 11 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for GPT-5.2-Codex and Qwen3.5 Plus 2026-04-20
BenchmarkGPT-5.2-CodexQwen3.5 Plus 2026-04-20Leader
Neither model has a result on 9 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
General benchmarks for GPT-5.2-Codex and Qwen3.5 Plus 2026-04-20
BenchmarkGPT-5.2-CodexQwen3.5 Plus 2026-04-20Leader
SAGE (Vals AI)Not measured30.4%Only Qwen3.5 Plus 2026-04-20 measured
IFBench77.6%Not measuredOnly GPT-5.2-Codex measured
Long context reasoning (AA-LCR)82.3%Not measuredOnly GPT-5.2-Codex measured
DTBenchNot measured80.5%Only Qwen3.5 Plus 2026-04-20 measured
LMCANot measured36.4%Only Qwen3.5 Plus 2026-04-20 measured
CL-benchNot measured19.8%Only Qwen3.5 Plus 2026-04-20 measured
CL-bench LifeNot measured12.4%Only Qwen3.5 Plus 2026-04-20 measured
Neither model has a result on the other 39 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5.2-Codex and Qwen3.5 Plus 2026-04-20
BenchmarkGPT-5.2-CodexQwen3.5 Plus 2026-04-20Leader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

GPT-5.2-Codex$0.0088Fits in one request
Qwen3.5 Plus 2026-04-20$0.0012Fits in one request

Qwen3.5 Plus 2026-04-20 costs less

Repository review

50K input + 3K output tokens

GPT-5.2-Codex$0.130Fits in one request
Qwen3.5 Plus 2026-04-20$0.020Fits in one request

Qwen3.5 Plus 2026-04-20 costs less

Agent loop

200K input + 10K output tokens

GPT-5.2-Codex$0.490Fits in one request
Qwen3.5 Plus 2026-04-20$0.078Fits in one request

Qwen3.5 Plus 2026-04-20 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of GPT-5.2-Codex and Qwen3.5 Plus 2026-04-20
SpecificationOpenAI GPT-5.2-CodexQwen3.5 Plus 2026-04-20
MakerOpenAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedJanuary 14, 2026April 27, 2026
Context window400K1M
Input $/Mtok$1.75$0.30
Output $/Mtok$14.00$1.80
Coding index45.439.5
Independent measurements behind it32
Cost per solved task$0.43$1.35
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.2-Codex better than Qwen3.5 Plus 2026-04-20 for coding?

Pick GPT-5.2-Codex for coding: it scores 45.4 on the Vibe Coding Index against 39.5 for Qwen3.5 Plus 2026-04-20. Pick Qwen3.5 Plus 2026-04-20 for output tokens 7.8x cheaper ($1.80 vs $14.00 per million) and a larger context window (1M against 400K tokens).

Which is cheaper, GPT-5.2-Codex or Qwen3.5 Plus 2026-04-20?

GPT-5.2-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Qwen3.5 Plus 2026-04-20 costs $0.30 and $1.80. Per solved SWE-bench Verified task, GPT-5.2-Codex costs $0.43 and Qwen3.5 Plus 2026-04-20 $1.35.

Which has the bigger context window, GPT-5.2-Codex or Qwen3.5 Plus 2026-04-20?

Qwen3.5 Plus 2026-04-20, with 1M tokens against 400K.

How many benchmarks is the GPT-5.2-Codex vs Qwen3.5 Plus 2026-04-20 comparison based on?

4 benchmarks have a result for both models as of October 22, 2026. GPT-5.2-Codex's coding index rests on 3 independent benchmarks and Qwen3.5 Plus 2026-04-20's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gpt-5-2-codex-vs-qwen3-5-plus-20260420">LLMBenchmark.ai, GPT-5.2-Codex vs Qwen3.5 Plus 2026-04-20</a></p>