GLM 5.3 FlashX vs GPT-5 Pro
GLM 5.3 FlashX costs 96.0x less per output token than GPT-5 Pro ($1.25 vs $120.00 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.25
- Coding
- No data
- Overall
- No data
- Output $/M
- $120.00
GLM 5.3 FlashX or GPT-5 Pro: 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 96.0x cheaper ($1.25 vs $120.00 per million) and a larger context window (1.05M against 400K tokens).
No benchmark has tested both yet. GLM 5.3 FlashX has none yet; GPT-5 Pro on WeirdML, Epoch Capabilities Index and ARC-AGI. 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Long documents
Listed context window
GLM 5.3 FlashX
GLM 5.3 FlashX takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3 FlashX
GLM 5.3 FlashX $0.0010, GPT-5 Pro $0.075 per turn.
List prices
At a glance
- Coding index
- GLM 5.3 FlashX not benchmarked, GPT-5 Pro 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-5 Pro $120.00 per million output tokens, 96.0x apart.
- Context window
- GLM 5.3 FlashX takes 1.05M tokens, GPT-5 Pro 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 Index1 board measured
| Benchmark | GLM 5.3 FlashX | GPT-5 Pro | Leader |
|---|---|---|---|
| WeirdML | Not measured | 60.4% | Only GPT-5 Pro measured |
| Neither model has a result on the other 38 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GLM 5.3 FlashX | GPT-5 Pro | Leader |
|---|---|---|---|
| Epoch Capabilities Index | Not measured | 150.6 | Only GPT-5 Pro measured |
| Neither model has a result on the other 1 board here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GLM 5.3 FlashX | GPT-5 Pro | Leader |
|---|---|---|---|
| ARC-AGI | Not measured | 70.2% | Only GPT-5 Pro measured |
| ARC-AGI-2 | Not measured | 18.3% | Only GPT-5 Pro measured |
| SimpleBench | Not measured | 61.6% | Only GPT-5 Pro measured |
| Chess puzzles | Not measured | 48.0% | Only GPT-5 Pro measured |
| Kagi LLM Benchmark | Not measured | 76.8% | Only GPT-5 Pro measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GLM 5.3 FlashX | GPT-5 Pro | Leader |
|---|---|---|---|
| FrontierMath, tiers 1 to 3 | Not measured | 55.8% | Only GPT-5 Pro measured |
| FrontierMath, tier 4 | Not measured | 19.5% | Only GPT-5 Pro measured |
| Neither model has a result on the other 11 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 FlashX costs less
Repository review
50K input + 3K output tokens
GLM 5.3 FlashX costs less
Agent loop
200K input + 10K output tokens
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.
| Specification | Z.ai GLM 5.3 FlashX | OpenAI GPT-5 Pro |
|---|---|---|
| Maker | Z.ai | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | September 18, 2026 | October 6, 2025 |
| Context window | 1.05M | 400K |
| Input $/Mtok | $0.37 | $15.00 |
| Output $/Mtok | $1.25 | $120.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5.3 FlashX better than GPT-5 Pro 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 96.0x cheaper ($1.25 vs $120.00 per million) and a larger context window (1.05M against 400K tokens).
Which is cheaper, GLM 5.3 FlashX or GPT-5 Pro?
GLM 5.3 FlashX costs $0.37 per million input tokens and $1.25 per million output tokens; GPT-5 Pro costs $15.00 and $120.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5.3 FlashX or GPT-5 Pro?
GLM 5.3 FlashX, with 1.05M tokens against 400K.
Has any benchmark tested both GLM 5.3 FlashX and GPT-5 Pro?
No benchmark has tested both yet. GLM 5.3 FlashX has none yet; GPT-5 Pro on WeirdML, Epoch Capabilities Index and ARC-AGI. Compare them on price and context instead. Data as of October 21, 2026.