GLM 5.3 FlashX vs Qwen3.8 2.4T A95B
GLM 5.3 FlashX costs 4.8x less per output token than Qwen3.8 2.4T A95B ($1.25 vs $6.00 per million). Updated October 22, 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
- $6.00
GLM 5.3 FlashX or Qwen3.8 2.4T A95B: 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 4.8x cheaper ($1.25 vs $6.00 per million).
No benchmark has tested both yet. GLM 5.3 FlashX has none yet; Qwen3.8 2.4T A95B on AA Coding Index, SciCode and AA Intelligence Index. 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
Intelligence
AA Intelligence Index
No call
Only Qwen3.8 2.4T A95B has a AA Intelligence Index result, 39.9.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.8 2.4T A95B has a AA Agentic Index result, 50.1.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3 FlashX
GLM 5.3 FlashX $0.0010, Qwen3.8 2.4T A95B $0.0050 per turn.
List prices
At a glance
- Coding index
- GLM 5.3 FlashX not benchmarked, Qwen3.8 2.4T A95B 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 Qwen3.8 2.4T A95B $6.00 per million output tokens, 4.8x apart.
- Context window
- Both take 1.05M tokens.
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 Index2 boards measured
| Benchmark | GLM 5.3 FlashX | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 71.9 | Only Qwen3.8 2.4T A95B measured |
| SciCode | Not measured | 54.1% | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 37 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GLM 5.3 FlashX | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 39.9 | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GLM 5.3 FlashX | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 50.1 | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | GLM 5.3 FlashX | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 93.5% | Only Qwen3.8 2.4T A95B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 42.4% | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 20 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GLM 5.3 FlashX | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 80.3% | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 45 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 | Qwen3.8 2.4T A95B |
|---|---|---|
| Maker | Z.ai | Qwen |
| Weights | No public weights listed | Open weights |
| Released | September 18, 2026 | August 12, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.37 | $2.00 |
| Output $/Mtok | $1.25 | $6.00 |
| 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 Qwen3.8 2.4T A95B 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 4.8x cheaper ($1.25 vs $6.00 per million).
Which is cheaper, GLM 5.3 FlashX or Qwen3.8 2.4T A95B?
GLM 5.3 FlashX costs $0.37 per million input tokens and $1.25 per million output tokens; Qwen3.8 2.4T A95B costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5.3 FlashX or Qwen3.8 2.4T A95B?
Neither: both take 1.05M tokens.
Has any benchmark tested both GLM 5.3 FlashX and Qwen3.8 2.4T A95B?
No benchmark has tested both yet. GLM 5.3 FlashX has none yet; Qwen3.8 2.4T A95B on AA Coding Index, SciCode and AA Intelligence Index. Compare them on price and context instead. Data as of October 22, 2026.