GLM 5.3 FlashX vs Ling 3.0 Flash
Ling 3.0 Flash costs 10.3x less per output token than GLM 5.3 FlashX ($0.1215 vs $1.25 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.25
- Coding
- 29.6
- Overall
- No data
- Output $/M
- $0.1215
GLM 5.3 FlashX or Ling 3.0 Flash: which to pick
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; GLM 5.3 FlashX has none, so the two cannot be ranked on coding.
Pick GLM 5.3 FlashX for a larger context window (1.05M against 262K tokens).
No benchmark has tested both yet. GLM 5.3 FlashX has none yet; Ling 3.0 Flash on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Ling 3.0 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Ling 3.0 Flash has a AA Intelligence Index result, 20.1.
Directional only
Agentic work
AA Agentic Index
No call
Only Ling 3.0 Flash has a AA Agentic Index result, 19.3.
Directional only
Reasoning
GPQA Diamond
No call
Only Ling 3.0 Flash has a GPQA Diamond result, 84.8%.
Directional only
Knowledge
MMLU Pro
No call
Only Ling 3.0 Flash has a MMLU Pro result, 82.0%.
Directional only
Long documents
Listed context window
GLM 5.3 FlashX
GLM 5.3 FlashX takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
GLM 5.3 FlashX $0.0010, Ling 3.0 Flash $0.0001 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Ling 3.0 Flash has the number, $0.05.
Directional only
At a glance
- Coding index
- GLM 5.3 FlashX not benchmarked, Ling 3.0 Flash 29.6 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 FlashX $1.25 against Ling 3.0 Flash $0.1215 per million output tokens, 10.3x apart.
- Context window
- GLM 5.3 FlashX takes 1.05M tokens, Ling 3.0 Flash 262K.
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 Index8 boards measured
| Benchmark | GLM 5.3 FlashX | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 50.6 | Only Ling 3.0 Flash measured |
| LiveCodeBench (Vals AI) | Not measured | 84.0% | Only Ling 3.0 Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 65.2% | Only Ling 3.0 Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 2.9% | Only Ling 3.0 Flash measured |
| Code migration (Vals AI) | Not measured | 0.0% | Only Ling 3.0 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 50.2% | Only Ling 3.0 Flash measured |
| SkillsBench (Vals AI) | Not measured | 27.9% | Only Ling 3.0 Flash measured |
| SciCode | Not measured | 42.0% | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | GLM 5.3 FlashX | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 20.1 | Only Ling 3.0 Flash 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
| Benchmark | GLM 5.3 FlashX | Ling 3.0 Flash | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 19.3 | Only Ling 3.0 Flash measured |
| Finance Agent (Vals AI) | Not measured | 30.3% | Only Ling 3.0 Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 0.0% | Only Ling 3.0 Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 25.0% | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 37 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GLM 5.3 FlashX | Ling 3.0 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 84.8% | Only Ling 3.0 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 85.5% | Only Ling 3.0 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 23.7% | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 19 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | GLM 5.3 FlashX | Ling 3.0 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 82.0% | Only Ling 3.0 Flash measured |
| LegalBench (Vals AI) | Not measured | 79.7% | Only Ling 3.0 Flash measured |
| CorpFin (Vals AI) | Not measured | 61.9% | Only Ling 3.0 Flash measured |
| TaxEval (Vals AI) | Not measured | 70.7% | Only Ling 3.0 Flash measured |
| MedCode (Vals AI) | Not measured | 32.3% | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 13 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | GLM 5.3 FlashX | Ling 3.0 Flash | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | Not measured | 50.7% | Only Ling 3.0 Flash measured |
| MedScribe (Vals AI) | Not measured | 80.9% | Only Ling 3.0 Flash measured |
| Long context reasoning (AA-LCR) | Not measured | 73.0% | Only Ling 3.0 Flash measured |
| Neither model has a result on the other 43 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
Ling 3.0 Flash costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 Flash 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 | inclusionAI Ling 3.0 Flash |
|---|---|---|
| Maker | Z.ai | inclusionAI |
| Weights | No public weights listed | Open weights |
| Released | September 18, 2026 | July 23, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.37 | $0.0405 |
| Output $/Mtok | $1.25 | $0.1215 |
| Coding index | Not benchmarked | 29.6 |
| Independent measurements behind it | 0 | 2 |
| Cost per solved task | Not computable | $0.05 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5.3 FlashX better than Ling 3.0 Flash for coding?
Only Ling 3.0 Flash has a coding score, 29.6 on the Vibe Coding Index; GLM 5.3 FlashX has none, so the two cannot be ranked on coding. Pick GLM 5.3 FlashX for a larger context window (1.05M against 262K tokens).
Which is cheaper, GLM 5.3 FlashX or Ling 3.0 Flash?
GLM 5.3 FlashX costs $0.37 per million input tokens and $1.25 per million output tokens; Ling 3.0 Flash costs $0.0405 and $0.1215. Cost per solved task is known for Ling 3.0 Flash only.
Which has the bigger context window, GLM 5.3 FlashX or Ling 3.0 Flash?
GLM 5.3 FlashX, with 1.05M tokens against 262K.
Has any benchmark tested both GLM 5.3 FlashX and Ling 3.0 Flash?
No benchmark has tested both yet. GLM 5.3 FlashX has none yet; Ling 3.0 Flash on AA Coding Index, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI). Compare them on price and context instead. Data as of October 22, 2026.