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GLM 5.3 FlashX vs GPT-3.5 Turbo 16k

GLM 5.3 FlashX costs 3.2x less per output token than GPT-3.5 Turbo 16k ($1.25 vs $4.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Replace GLM 5.3 FlashX Replace GPT-3.5 Turbo 16k
GLM 5.3 FlashXZ.ai
Coding
No data
Overall
No data
Output $/M
$1.25
GPT-3.5 Turbo 16kOpenAI
Coding
No data
Overall
No data
Output $/M
$4.00
vs $1.25 vs $4.00 per 1M output tokens. GLM 5.3 FlashX is 3.2x cheaper.

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

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

Pick GLM 5.3 FlashX for output tokens 3.2x cheaper ($1.25 vs $4.00 per million) and a larger context window (1.05M against 16K tokens).

Model AGLM 5.3 FlashXZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-3.5 Turbo 16kOpenAINot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested either model yet, so price and context are the only way to compare them.

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 FlashX not benchmarked, GPT-3.5 Turbo 16k 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 FlashX $1.25 against GPT-3.5 Turbo 16k $4.00 per million output tokens, 3.2x apart.
Context window
GLM 5.3 FlashX takes 1.05M tokens, GPT-3.5 Turbo 16k 16K.

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.

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 FlashX$0.0010Fits in one request
GPT-3.5 Turbo 16k$0.0050Fits in one request

GLM 5.3 FlashX costs less

Repository review

50K input + 3K output tokens

GLM 5.3 FlashX$0.022Fits in one request
GPT-3.5 Turbo 16k$0.162Exceeds the context window

GLM 5.3 FlashX costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 FlashX$0.086Fits in one request
GPT-3.5 Turbo 16k$0.640Exceeds the context window

GLM 5.3 FlashX 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 FlashX and GPT-3.5 Turbo 16k
SpecificationZ.ai GLM 5.3 FlashXOpenAI GPT-3.5 Turbo 16k
MakerZ.aiOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 18, 2026August 28, 2023
Context window1.05M16K
Input $/Mtok$0.37$3.00
Output $/Mtok$1.25$4.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

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

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 5.3 FlashX for output tokens 3.2x cheaper ($1.25 vs $4.00 per million) and a larger context window (1.05M against 16K tokens).

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

GLM 5.3 FlashX costs $0.37 per million input tokens and $1.25 per million output tokens; GPT-3.5 Turbo 16k costs $3.00 and $4.00. Cost per solved task is known for neither of them.

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

GLM 5.3 FlashX, with 1.05M tokens against 16K.

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

No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 22, 2026.

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