Enter opens the highlighted result. Esc closes.

GPT-3.5 Turbo 16k vs GPT-5.3-Codex

GPT-3.5 Turbo 16k costs 3.5x less per output token than GPT-5.3-Codex ($4.00 vs $14.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Replace GPT-3.5 Turbo 16k Replace GPT-5.3-Codex
GPT-3.5 Turbo 16kOpenAI
Coding
No data
Overall
No data
Output $/M
$4.00
GPT-5.3-CodexOpenAI
Coding
60.0
Overall
No data
Output $/M
$14.00
vs $4.00 vs $14.00 per 1M output tokens. GPT-3.5 Turbo 16k is 3.5x cheaper.

GPT-3.5 Turbo 16k or GPT-5.3-Codex: which to pick

Only GPT-5.3-Codex has a coding score, 60.0 on the Vibe Coding Index; GPT-3.5 Turbo 16k has none, so the two cannot be ranked on coding.

Pick GPT-3.5 Turbo 16k for output tokens 3.5x cheaper ($4.00 vs $14.00 per million).

Model AGPT-3.5 Turbo 16kOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-5.3-CodexOpenAI60.0/1003 independent benchmarks$0.59 per solved task

No benchmark has tested both yet. GPT-3.5 Turbo 16k has none yet; GPT-5.3-Codex on LMArena WebDev, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI). Compare them on price and context instead.

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-3.5 Turbo 16k not benchmarked, GPT-5.3-Codex 60.0 from 3 benchmarks.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
GPT-3.5 Turbo 16k $4.00 against GPT-5.3-Codex $14.00 per million output tokens, 3.5x apart.
Context window
GPT-3.5 Turbo 16k takes 16K tokens, GPT-5.3-Codex 400K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

CodingDirectional onlySix of these boards feed the Vibe Coding Index12 boards measured
Coding benchmarks for GPT-3.5 Turbo 16k and GPT-5.3-Codex
BenchmarkGPT-3.5 Turbo 16kGPT-5.3-CodexLeader
LMArena WebDevNot measured1407Only GPT-5.3-Codex measured
LiveCodeBench (Vals AI)Not measured87.3%Only GPT-5.3-Codex measured
SWE-bench Verified (Vals AI)Not measured78.0%Only GPT-5.3-Codex measured
Vibe Code Bench (Vals AI)Not measured61.8%Only GPT-5.3-Codex measured
IOI (Vals AI)Not measured53.8%Only GPT-5.3-Codex measured
Terminal-Bench Hard (Artificial Analysis run)Not measured53.0%Only GPT-5.3-Codex measured
Terminal-BenchNot measured78.4%Only GPT-5.3-Codex measured
WeirdMLNot measured79.3%Only GPT-5.3-Codex measured
ALE-BenchNot measured1655.2Only GPT-5.3-Codex measured
LMArena WebDev: ReactNot measured1395Only GPT-5.3-Codex measured
LMArena WebDev: HTMLNot measured1422Only GPT-5.3-Codex measured
LMArena WebDev: from an imageNot measured1443Only GPT-5.3-Codex measured
Neither model has a result on the other 27 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Intelligence benchmarks for GPT-3.5 Turbo 16k and GPT-5.3-Codex
BenchmarkGPT-3.5 Turbo 16kGPT-5.3-CodexLeader
AA Intelligence IndexNot measured32.5Only GPT-5.3-Codex measured
Epoch Capabilities IndexNot measured157.1Only GPT-5.3-Codex measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
Agentic work benchmarks for GPT-3.5 Turbo 16k and GPT-5.3-Codex
BenchmarkGPT-3.5 Turbo 16kGPT-5.3-CodexLeader
Design Arena: agents building web appsNot measured1032Only GPT-5.3-Codex measured
Design Arena: agents building full-stack appsNot measured983Only GPT-5.3-Codex measured
Design Arena: agents building mobile appsNot measured1053Only GPT-5.3-Codex measured
Design Arena: agents building Android appsNot measured1084Only GPT-5.3-Codex measured
Design Arena: agents building Godot gamesNot measured1124Only GPT-5.3-Codex measured
τ²-Bench TelecomNot measured86.0%Only GPT-5.3-Codex measured
METR time horizonsNot measured74.5%Only GPT-5.3-Codex measured
Vending-Bench 2Not measured$5,940Only GPT-5.3-Codex measured
Neither model has a result on the other 33 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Reasoning benchmarks for GPT-3.5 Turbo 16k and GPT-5.3-Codex
BenchmarkGPT-3.5 Turbo 16kGPT-5.3-CodexLeader
GPQA Diamond (Artificial Analysis run)Not measured91.5%Only GPT-5.3-Codex measured
Humanity's Last Exam (Artificial Analysis run)Not measured42.5%Only GPT-5.3-Codex measured
Neither model has a result on the other 20 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
Web design benchmarks for GPT-3.5 Turbo 16k and GPT-5.3-Codex
BenchmarkGPT-3.5 Turbo 16kGPT-5.3-CodexLeader
Design Arena: websitesNot measured1162Only GPT-5.3-Codex measured
Design Arena: UI componentsNot measured1134Only GPT-5.3-Codex measured
Design Arena: game devNot measured1161Only GPT-5.3-Codex measured
Design Arena: data vizNot measured1164Only GPT-5.3-Codex measured
Design Arena: 3DNot measured1007Only GPT-5.3-Codex measured
Design Arena: all code categoriesNot measured1144Only GPT-5.3-Codex measured
Design Arena: SVGNot measured1129Only GPT-5.3-Codex measured
Design Arena: ASCII artNot measured1152Only GPT-5.3-Codex measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
General benchmarks for GPT-3.5 Turbo 16k and GPT-5.3-Codex
BenchmarkGPT-3.5 Turbo 16kGPT-5.3-CodexLeader
IFBenchNot measured75.4%Only GPT-5.3-Codex measured
Long context reasoning (AA-LCR)Not measured83.3%Only GPT-5.3-Codex measured
Neither model has a result on the other 44 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-3.5 Turbo 16k$0.0050Fits in one request
GPT-5.3-Codex$0.0088Fits in one request

GPT-3.5 Turbo 16k costs less

Repository review

50K input + 3K output tokens

GPT-3.5 Turbo 16k$0.162Exceeds the context window
GPT-5.3-Codex$0.130Fits in one request

GPT-5.3-Codex costs less

Agent loop

200K input + 10K output tokens

GPT-3.5 Turbo 16k$0.640Exceeds the context window
GPT-5.3-Codex$0.490Fits in one request

GPT-5.3-Codex 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-3.5 Turbo 16k and GPT-5.3-Codex
SpecificationOpenAI GPT-3.5 Turbo 16kOpenAI GPT-5.3-Codex
MakerOpenAIOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedAugust 28, 2023February 24, 2026
Context window16K400K
Input $/Mtok$3.00$1.75
Output $/Mtok$4.00$14.00
Coding indexNot benchmarked60.0
Independent measurements behind it03
Cost per solved taskNot computable$0.59
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-3.5 Turbo 16k better than GPT-5.3-Codex for coding?

Only GPT-5.3-Codex has a coding score, 60.0 on the Vibe Coding Index; GPT-3.5 Turbo 16k has none, so the two cannot be ranked on coding. Pick GPT-3.5 Turbo 16k for output tokens 3.5x cheaper ($4.00 vs $14.00 per million).

Which is cheaper, GPT-3.5 Turbo 16k or GPT-5.3-Codex?

GPT-3.5 Turbo 16k costs $3.00 per million input tokens and $4.00 per million output tokens; GPT-5.3-Codex costs $1.75 and $14.00. Cost per solved task is known for GPT-5.3-Codex only.

Which has the bigger context window, GPT-3.5 Turbo 16k or GPT-5.3-Codex?

GPT-5.3-Codex, with 400K tokens against 16K.

Has any benchmark tested both GPT-3.5 Turbo 16k and GPT-5.3-Codex?

No benchmark has tested both yet. GPT-3.5 Turbo 16k has none yet; GPT-5.3-Codex on LMArena WebDev, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI). Compare them on price and context instead. Data as of October 22, 2026.

Compare next