Kimi K2 0711 vs Hunyuan A13B Instruct
Hunyuan A13B Instruct costs 4.0x less per output token than Kimi K2 0711 ($0.57 vs $2.30 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $2.30
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.57
Kimi K2 0711 or Hunyuan A13B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested both yet. Kimi K2 0711 has results on Aider polyglot, SWE-bench Verified and LiveCodeBench (Vals AI); 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
Intelligence
AA Intelligence Index
No call
Only Kimi K2 0711 has a AA Intelligence Index result, 12.7.
Directional only
Reasoning
GPQA Diamond
No call
Only Kimi K2 0711 has a GPQA Diamond result, 71.5%.
Directional only
Math
AIME
No call
Only Kimi K2 0711 has a AIME result, 62.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2 0711 has a MMLU Pro result, 79.4%.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2 0711 has a Design Arena: websites result, 1050.
Directional only
Long documents
Listed context window
No call
Both take 131K tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Hunyuan A13B Instruct
Kimi K2 0711 $0.0017, Hunyuan A13B Instruct $0.0004 per turn.
List prices
At a glance
- Coding index
- Kimi K2 0711 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
- Kimi K2 0711 $2.30 against Hunyuan A13B Instruct $0.57 per million output tokens, 4.0x apart.
- Context window
- Both take 131K 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 Index8 boards measured
| Benchmark | Kimi K2 0711 | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| Aider polyglot | 59.1% | Not measured | Only Kimi K2 0711 measured |
| SWE-bench Verified | 71.2% | Not measured | Only Kimi K2 0711 measured |
| LiveCodeBench (Vals AI) | 70.5% | Not measured | Only Kimi K2 0711 measured |
| LiveCodeBench (Artificial Analysis run) | 55.6% | Not measured | Only Kimi K2 0711 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | Not measured | Only Kimi K2 0711 measured |
| Terminal-Bench | 27.8% | Not measured | Only Kimi K2 0711 measured |
| GSO-Bench | 4.9% | Not measured | Only Kimi K2 0711 measured |
| WeirdML | 39.4% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 31 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Kimi K2 0711 | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.7 | Not measured | Only Kimi K2 0711 measured |
| Epoch Capabilities Index | 140.0 | Not measured | Only Kimi K2 0711 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Kimi K2 0711 | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 61.1% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Kimi K2 0711 | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 71.5% | Not measured | Only Kimi K2 0711 measured |
| GPQA Diamond (Artificial Analysis run) | 76.6% | Not measured | Only Kimi K2 0711 measured |
| Humanity's Last Exam (Artificial Analysis run) | 7.4% | Not measured | Only Kimi K2 0711 measured |
| SimpleBench | 26.3% | Not measured | Only Kimi K2 0711 measured |
| Kagi LLM Benchmark | 64.4% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Kimi K2 0711 | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| AIME | 62.7% | Not measured | Only Kimi K2 0711 measured |
| MATH 500 (Vals AI) | 94.2% | Not measured | Only Kimi K2 0711 measured |
| MGSM (Vals AI) | 91.0% | Not measured | Only Kimi K2 0711 measured |
| AA Math Index | 57.0 | Not measured | Only Kimi K2 0711 measured |
| AIME 2025 (Artificial Analysis run) | 57.0% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Kimi K2 0711 | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| MMLU Pro | 79.4% | Not measured | Only Kimi K2 0711 measured |
| LegalBench (Vals AI) | 81.5% | Not measured | Only Kimi K2 0711 measured |
| CorpFin (Vals AI) | 50.4% | Not measured | Only Kimi K2 0711 measured |
| TaxEval (Vals AI) | 70.2% | Not measured | Only Kimi K2 0711 measured |
| MedQA (Vals AI) | 84.0% | Not measured | Only Kimi K2 0711 measured |
| MMLU Pro (Artificial Analysis run) | 82.4% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Kimi K2 0711 | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1050 | Not measured | Only Kimi K2 0711 measured |
| Design Arena: UI components | 1027 | Not measured | Only Kimi K2 0711 measured |
| Design Arena: game dev | 973 | Not measured | Only Kimi K2 0711 measured |
| Design Arena: data viz | 1018 | Not measured | Only Kimi K2 0711 measured |
| Design Arena: all code categories | 1033 | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 4 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Kimi K2 0711 | Hunyuan A13B Instruct | Leader |
|---|---|---|---|
| IFBench | 41.5% | Not measured | Only Kimi K2 0711 measured |
| Long context reasoning (AA-LCR) | 53.0% | Not measured | Only Kimi K2 0711 measured |
| Fiction.LiveBench | 61.1% | Not measured | Only Kimi K2 0711 measured |
| Creative writing (Lech Mazur) | 85.6% | Not measured | Only Kimi K2 0711 measured |
| CL-bench | 11.9% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 41 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
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 | MoonshotAI Kimi K2 0711 | Tencent Hunyuan A13B Instruct |
|---|---|---|
| Maker | Moonshot AI | Tencent |
| Weights | Open weights | Open weights |
| Released | July 11, 2025 | July 8, 2025 |
| Context window | 131K | 131K |
| Input $/Mtok | $0.57 | $0.14 |
| Output $/Mtok | $2.30 | $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 Kimi K2 0711 better than Hunyuan A13B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Kimi K2 0711 or Hunyuan A13B Instruct?
Kimi K2 0711 costs $0.57 per million input tokens and $2.30 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, Kimi K2 0711 or Hunyuan A13B Instruct?
Neither: both take 131K tokens.
Has any benchmark tested both Kimi K2 0711 and Hunyuan A13B Instruct?
No benchmark has tested both yet. Kimi K2 0711 has results on Aider polyglot, SWE-bench Verified and LiveCodeBench (Vals AI); Hunyuan A13B Instruct has none yet. Compare them on price and context instead. Data as of October 22, 2026.