Qwen2.5 7B Instruct vs Hunyuan A13B Instruct
Qwen2.5 7B Instruct costs 2.8x less per output token than Hunyuan A13B Instruct ($0.20 vs $0.57 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.20
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.57
Qwen2.5 7B Instruct or Hunyuan A13B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Qwen2.5 7B Instruct for output tokens 2.8x cheaper ($0.20 vs $0.57 per million).
No benchmark has tested both yet. Qwen2.5 7B Instruct has results on Epoch Capabilities Index, BALROG and GPQA Diamond (Epoch AI run); Hunyuan A13B Instruct has none yet. 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
Hunyuan A13B Instruct
Hunyuan A13B Instruct takes 131K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 7B Instruct
Qwen2.5 7B Instruct $0.0002, Hunyuan A13B Instruct $0.0004 per turn.
List prices
At a glance
- Coding index
- Qwen2.5 7B Instruct 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
- Qwen2.5 7B Instruct $0.20 against Hunyuan A13B Instruct $0.57 per million output tokens, 2.8x apart.
- Context window
- Qwen2.5 7B Instruct takes 33K 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.
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen2.5 7B Instruct | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| Epoch Capabilities Index | 118.5 | Not measured | Only Qwen2.5 7B Instruct 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 | Qwen2.5 7B Instruct | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| BALROG | 7.8% | Not measured | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen2.5 7B Instruct | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond (Epoch AI run) | 35.5% | Not measured | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 21 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen2.5 7B Instruct | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| OTIS Mock AIME | 2.5% | Not measured | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen2.5 7B Instruct | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| MMLU | 72.9% | Not measured | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 17 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
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
Qwen2.5 7B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 7B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 7B 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 | Qwen2.5 7B Instruct | Tencent Hunyuan A13B Instruct |
|---|---|---|
| Maker | Qwen | Tencent |
| Weights | Open weights | Open weights |
| Released | October 16, 2024 | July 8, 2025 |
| Context window | 33K | 131K |
| Input $/Mtok | $0.10 | $0.14 |
| Output $/Mtok | $0.20 | $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 Qwen2.5 7B Instruct better than Hunyuan A13B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen2.5 7B Instruct for output tokens 2.8x cheaper ($0.20 vs $0.57 per million).
Which is cheaper, Qwen2.5 7B Instruct or Hunyuan A13B Instruct?
Qwen2.5 7B Instruct costs $0.10 per million input tokens and $0.20 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, Qwen2.5 7B Instruct or Hunyuan A13B Instruct?
Hunyuan A13B Instruct, with 131K tokens against 33K.
Has any benchmark tested both Qwen2.5 7B Instruct and Hunyuan A13B Instruct?
No benchmark has tested both yet. Qwen2.5 7B Instruct has results on Epoch Capabilities Index, BALROG and GPQA Diamond (Epoch AI run); Hunyuan A13B Instruct has none yet. Compare them on price and context instead. Data as of October 22, 2026.