GLM 5.3 Prime vs Hunyuan A13B Instruct
Hunyuan A13B Instruct costs 15.4x less per output token than GLM 5.3 Prime ($0.57 vs $8.80 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $8.80
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.57
GLM 5.3 Prime or Hunyuan A13B 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 131K tokens).
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.
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 Prime
GLM 5.3 Prime takes 1M tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hunyuan A13B Instruct
GLM 5.3 Prime $0.0072, Hunyuan A13B Instruct $0.0004 per turn.
List prices
At a glance
- Coding index
- GLM 5.3 Prime not benchmarked, Hunyuan A13B 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 Hunyuan A13B Instruct $0.57 per million output tokens, 15.4x apart.
- Context window
- GLM 5.3 Prime takes 1M tokens, Hunyuan A13B Instruct 131K.
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
Hunyuan A13B Instruct costs less
Repository review
50K input + 3K output tokens
Hunyuan A13B Instruct costs less
Agent loop
200K input + 10K output tokens
Hunyuan A13B 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.
| Specification | Z.ai GLM 5.3 Prime | Tencent Hunyuan A13B Instruct |
|---|---|---|
| Maker | Z.ai | Tencent |
| Weights | No public weights listed | Open weights |
| Released | September 23, 2026 | July 8, 2025 |
| Context window | 1M | 131K |
| Input $/Mtok | $2.80 | $0.14 |
| Output $/Mtok | $8.80 | $0.57 |
| 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 Prime better than Hunyuan A13B 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 131K tokens).
Which is cheaper, GLM 5.3 Prime or Hunyuan A13B Instruct?
GLM 5.3 Prime costs $2.80 per million input tokens and $8.80 per million output tokens; Hunyuan A13B Instruct costs $0.14 and $0.57. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5.3 Prime or Hunyuan A13B Instruct?
GLM 5.3 Prime, with 1M tokens against 131K.
Has any benchmark tested both GLM 5.3 Prime and Hunyuan A13B Instruct?
No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 22, 2026.