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GLM 5.3 Prime vs GPT-5.1-Codex

GLM 5.3 Prime and GPT-5.1-Codex cost about the same per output token ($8.80 vs $10.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.

Replace GLM 5.3 Prime Replace GPT-5.1-Codex
GLM 5.3 PrimeZ.ai
Coding
No data
Overall
No data
Output $/M
$8.80
GPT-5.1-CodexOpenAI
Coding
15.3
Overall
23.7
Output $/M
$10.00
vs $8.80 vs $10.00 per 1M output tokens. GLM 5.3 Prime is 1.1x cheaper.

GLM 5.3 Prime or GPT-5.1-Codex: which to pick

Only GPT-5.1-Codex has a coding score, 15.3 on the Vibe Coding Index; GLM 5.3 Prime has none, so the two cannot be ranked on coding.

Pick GLM 5.3 Prime for output tokens 1.1x cheaper ($8.80 vs $10.00 per million) and a larger context window (1M against 400K tokens).

Model AGLM 5.3 PrimeZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-5.1-CodexOpenAI15.3/1002 independent benchmarks$0.892 per solved task

No benchmark has tested both yet. GLM 5.3 Prime has none yet; GPT-5.1-Codex on SWE-bench Verified, LMArena WebDev and LiveCodeBench (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
GLM 5.3 Prime not benchmarked, GPT-5.1-Codex 15.3 from 2 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
GLM 5.3 Prime $8.80 against GPT-5.1-Codex $10.00 per million output tokens, 1.1x apart.
Context window
GLM 5.3 Prime takes 1M tokens, GPT-5.1-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 Index9 boards measured
Coding benchmarks for GLM 5.3 Prime and GPT-5.1-Codex
BenchmarkGLM 5.3 PrimeGPT-5.1-CodexLeader
SWE-bench VerifiedNot measured66.0%Only GPT-5.1-Codex measured
LMArena WebDevNot measured1337Only GPT-5.1-Codex measured
LiveCodeBench (Vals AI)Not measured85.5%Only GPT-5.1-Codex measured
Vibe Code Bench (Vals AI)Not measured13.1%Only GPT-5.1-Codex measured
LiveCodeBench (Artificial Analysis run)Not measured84.9%Only GPT-5.1-Codex measured
Terminal-Bench Hard (Artificial Analysis run)Not measured34.8%Only GPT-5.1-Codex measured
Terminal-BenchNot measured57.8%Only GPT-5.1-Codex measured
ALE-BenchNot measured1244.9Only GPT-5.1-Codex measured
LMArena WebDev: HTMLNot measured1346Only GPT-5.1-Codex measured
Neither model has a result on the other 29 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for GLM 5.3 Prime and GPT-5.1-Codex
BenchmarkGLM 5.3 PrimeGPT-5.1-CodexLeader
AA Intelligence IndexNot measured23.7Only GPT-5.1-Codex measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
Agentic work benchmarks for GLM 5.3 Prime and GPT-5.1-Codex
BenchmarkGLM 5.3 PrimeGPT-5.1-CodexLeader
Design Arena: agents building web appsNot measured1018Only GPT-5.1-Codex measured
Design Arena: agents building full-stack appsNot measured1086Only GPT-5.1-Codex measured
Design Arena: agents building mobile appsNot measured1191Only GPT-5.1-Codex measured
τ²-Bench TelecomNot measured83.0%Only GPT-5.1-Codex measured
Neither model has a result on the other 35 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Reasoning benchmarks for GLM 5.3 Prime and GPT-5.1-Codex
BenchmarkGLM 5.3 PrimeGPT-5.1-CodexLeader
GPQA Diamond (Artificial Analysis run)Not measured86.0%Only GPT-5.1-Codex measured
Humanity's Last Exam (Artificial Analysis run)Not measured25.7%Only GPT-5.1-Codex measured
Neither model has a result on the other 19 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Math benchmarks for GLM 5.3 Prime and GPT-5.1-Codex
BenchmarkGLM 5.3 PrimeGPT-5.1-CodexLeader
AA Math IndexNot measured95.7Only GPT-5.1-Codex measured
AIME 2025 (Artificial Analysis run)Not measured95.7%Only GPT-5.1-Codex measured
Neither model has a result on the other 11 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Knowledge benchmarks for GLM 5.3 Prime and GPT-5.1-Codex
BenchmarkGLM 5.3 PrimeGPT-5.1-CodexLeader
MMLU Pro (Artificial Analysis run)Not measured86.0%Only GPT-5.1-Codex measured
Neither model has a result on the other 16 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
Web design benchmarks for GLM 5.3 Prime and GPT-5.1-Codex
BenchmarkGLM 5.3 PrimeGPT-5.1-CodexLeader
Design Arena: websitesNot measured1162Only GPT-5.1-Codex measured
Design Arena: UI componentsNot measured1237Only GPT-5.1-Codex measured
Design Arena: game devNot measured1138Only GPT-5.1-Codex measured
Design Arena: data vizNot measured1213Only GPT-5.1-Codex measured
Design Arena: all code categoriesNot measured1152Only GPT-5.1-Codex measured
Neither model has a result on the other 4 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
General benchmarks for GLM 5.3 Prime and GPT-5.1-Codex
BenchmarkGLM 5.3 PrimeGPT-5.1-CodexLeader
IFBenchNot measured70.0%Only GPT-5.1-Codex measured
Long context reasoning (AA-LCR)Not measured69.3%Only GPT-5.1-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

GLM 5.3 Prime$0.0072Fits in one request
GPT-5.1-Codex$0.0063Fits in one request

GPT-5.1-Codex costs less

Repository review

50K input + 3K output tokens

GLM 5.3 Prime$0.166Fits in one request
GPT-5.1-Codex$0.092Fits in one request

GPT-5.1-Codex costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 Prime$0.648Fits in one request
GPT-5.1-Codex$0.350Fits in one request

GPT-5.1-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 GLM 5.3 Prime and GPT-5.1-Codex
SpecificationZ.ai GLM 5.3 PrimeOpenAI GPT-5.1-Codex
MakerZ.aiOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 23, 2026November 13, 2025
Context window1M400K
Input $/Mtok$2.80$1.25
Output $/Mtok$8.80$10.00
Coding indexNot benchmarked15.3
Independent measurements behind it02
Cost per solved taskNot computable$0.892
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 Prime better than GPT-5.1-Codex for coding?

Only GPT-5.1-Codex has a coding score, 15.3 on the Vibe Coding Index; GLM 5.3 Prime has none, so the two cannot be ranked on coding. Pick GLM 5.3 Prime for output tokens 1.1x cheaper ($8.80 vs $10.00 per million) and a larger context window (1M against 400K tokens).

Which is cheaper, GLM 5.3 Prime or GPT-5.1-Codex?

GLM 5.3 Prime costs $2.80 per million input tokens and $8.80 per million output tokens; GPT-5.1-Codex costs $1.25 and $10.00. Cost per solved task is known for GPT-5.1-Codex only.

Which has the bigger context window, GLM 5.3 Prime or GPT-5.1-Codex?

GLM 5.3 Prime, with 1M tokens against 400K.

Has any benchmark tested both GLM 5.3 Prime and GPT-5.1-Codex?

No benchmark has tested both yet. GLM 5.3 Prime has none yet; GPT-5.1-Codex on SWE-bench Verified, LMArena WebDev and LiveCodeBench (Vals AI). Compare them on price and context instead. Data as of October 21, 2026.

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