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GLM 5.3 Prime vs GPT-3.5 Turbo Instruct

GPT-3.5 Turbo Instruct costs 4.4x less per output token than GLM 5.3 Prime ($2.00 vs $8.80 per million). Updated October 22, 2026; no benchmark has tested both models yet.

GLM 5.3 PrimeZ.ai
Coding
No data
Overall
No data
Output $/M
$8.80
GPT-3.5 Turbo InstructOpenAI
Coding
No data
Overall
No data
Output $/M
$2.00
vs $8.80 vs $2.00 per 1M output tokens. GPT-3.5 Turbo Instruct is 4.4x cheaper.

GLM 5.3 Prime or GPT-3.5 Turbo Instruct: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GLM 5.3 Prime for a larger context window (1M against 4K tokens).

No benchmark has tested both yet. GLM 5.3 Prime has none yet; GPT-3.5 Turbo Instruct on METR time horizons. 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-3.5 Turbo Instruct not benchmarked.
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-3.5 Turbo Instruct $2.00 per million output tokens, 4.4x apart.
Context window
GLM 5.3 Prime takes 1M tokens, GPT-3.5 Turbo Instruct 4K.

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.

Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Agentic work benchmarks for GLM 5.3 Prime and GPT-3.5 Turbo Instruct
BenchmarkGLM 5.3 PrimeGPT-3.5 Turbo InstructLeader
METR time horizonsNot measured21.5%Only GPT-3.5 Turbo Instruct measured
Neither model has a result on the other 40 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-3.5 Turbo Instruct$0.0025Fits in one request

GPT-3.5 Turbo Instruct costs less

Repository review

50K input + 3K output tokens

GLM 5.3 Prime$0.166Fits in one request
GPT-3.5 Turbo Instruct$0.081Exceeds the context window

GPT-3.5 Turbo Instruct costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 Prime$0.648Fits in one request
GPT-3.5 Turbo Instruct$0.320Exceeds the context window

GPT-3.5 Turbo Instruct 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-3.5 Turbo Instruct
SpecificationZ.ai GLM 5.3 PrimeOpenAI GPT-3.5 Turbo Instruct
MakerZ.aiOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 23, 2026September 28, 2023
Context window1M4K
Input $/Mtok$2.80$1.50
Output $/Mtok$8.80$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 Prime better than GPT-3.5 Turbo Instruct for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5.3 Prime for a larger context window (1M against 4K tokens).

Which is cheaper, GLM 5.3 Prime or GPT-3.5 Turbo Instruct?

GLM 5.3 Prime costs $2.80 per million input tokens and $8.80 per million output tokens; GPT-3.5 Turbo Instruct costs $1.50 and $2.00. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 5.3 Prime or GPT-3.5 Turbo Instruct?

GLM 5.3 Prime, with 1M tokens against 4K.

Has any benchmark tested both GLM 5.3 Prime and GPT-3.5 Turbo Instruct?

No benchmark has tested both yet. GLM 5.3 Prime has none yet; GPT-3.5 Turbo Instruct on METR time horizons. Compare them on price and context instead. Data as of October 22, 2026.

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