Kimi K2 0905 vs Qwen-Plus
Qwen-Plus costs 3.2x less per output token than Kimi K2 0905 ($0.78 vs $2.50 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- 15.3
- Output $/M
- $2.50
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.78
Kimi K2 0905 or Qwen-Plus: 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 0905 has results on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and WeirdML; Qwen-Plus on LMArena Text: coding, LMArena Text: software and IT and GPQA Diamond (Epoch AI run). 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 0905 has a AA Intelligence Index result, 15.3.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2 0905 has a Design Arena: websites result, 1089.
Directional only
Long documents
Listed context window
Qwen-Plus
Qwen-Plus takes 1M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen-Plus
Kimi K2 0905 $0.0019, Qwen-Plus $0.0006 per turn.
List prices
At a glance
- Coding index
- Kimi K2 0905 not benchmarked, Qwen-Plus 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 0905 $2.50 against Qwen-Plus $0.78 per million output tokens, 3.2x apart.
- Context window
- Kimi K2 0905 takes 262K tokens, Qwen-Plus 1M.
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 Index6 boards measured
| Benchmark | Kimi K2 0905 | Qwen-Plus | Leader |
|---|---|---|---|
| LiveCodeBench (Artificial Analysis run) | 61.0% | Not measured | Only Kimi K2 0905 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 23.5% | Not measured | Only Kimi K2 0905 measured |
| WeirdML | 36.7% | Not measured | Only Kimi K2 0905 measured |
| ALE-Bench | 267.1 | Not measured | Only Kimi K2 0905 measured |
| LMArena Text: coding | Not measured | 1328 | Only Qwen-Plus measured |
| LMArena Text: software and IT | Not measured | 1343 | Only Qwen-Plus measured |
| Neither model has a result on the other 32 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Kimi K2 0905 | Qwen-Plus | Leader |
|---|---|---|---|
| AA Intelligence Index | 15.3 | Not measured | Only Kimi K2 0905 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 | Kimi K2 0905 | Qwen-Plus | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 73.4% | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Kimi K2 0905 | Qwen-Plus | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 76.7% | Not measured | Only Kimi K2 0905 measured |
| Humanity's Last Exam (Artificial Analysis run) | 6.4% | Not measured | Only Kimi K2 0905 measured |
| GPQA Diamond (Epoch AI run) | Not measured | 48.1% | Only Qwen-Plus measured |
| LMArena Text: hard prompts | Not measured | 1317 | Only Qwen-Plus measured |
| LMArena Text: expert | Not measured | 1328 | Only Qwen-Plus measured |
| LMArena Text: hard prompts in English | Not measured | 1333 | Only Qwen-Plus measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Kimi K2 0905 | Qwen-Plus | Leader |
|---|---|---|---|
| AA Math Index | 57.3 | Not measured | Only Kimi K2 0905 measured |
| AIME 2025 (Artificial Analysis run) | 57.3% | Not measured | Only Kimi K2 0905 measured |
| OTIS Mock AIME | Not measured | 17.8% | Only Qwen-Plus measured |
| MATH level 5 | Not measured | 65.3% | Only Qwen-Plus measured |
| LMArena Text: math | Not measured | 1326 | Only Qwen-Plus measured |
| LMArena Text: mathematical work | Not measured | 1332 | Only Qwen-Plus measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards measured
| Benchmark | Kimi K2 0905 | Qwen-Plus | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 81.9% | Not measured | Only Kimi K2 0905 measured |
| LMArena Text: science | Not measured | 1352 | Only Qwen-Plus measured |
| LMArena Text: medicine and healthcare | Not measured | 1350 | Only Qwen-Plus measured |
| LMArena Text: legal and government | Not measured | 1349 | Only Qwen-Plus measured |
| LMArena Text: business and finance | Not measured | 1303 | Only Qwen-Plus measured |
| Neither model has a result on the other 12 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Kimi K2 0905 | Qwen-Plus | Leader |
|---|---|---|---|
| Design Arena: websites | 1089 | Not measured | Only Kimi K2 0905 measured |
| Design Arena: all code categories | 1098 | Not measured | Only Kimi K2 0905 measured |
| Neither model has a result on the other 7 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index17 boards measured
| Benchmark | Kimi K2 0905 | Qwen-Plus | Leader |
|---|---|---|---|
| IFBench | 41.7% | Not measured | Only Kimi K2 0905 measured |
| Long context reasoning (AA-LCR) | 53.0% | Not measured | Only Kimi K2 0905 measured |
| DTBench | Not measured | 81.1% | Only Qwen-Plus measured |
| LMCA | Not measured | 24.0% | Only Qwen-Plus measured |
| Fiction.LiveBench | 66.7% | Not measured | Only Kimi K2 0905 measured |
| LMArena Text | Not measured | 1326 | Only Qwen-Plus measured |
| LMArena Text: instruction following | Not measured | 1303 | Only Qwen-Plus measured |
| LMArena Text: creative writing | Not measured | 1292 | Only Qwen-Plus measured |
| LMArena Text: English | Not measured | 1339 | Only Qwen-Plus measured |
| LMArena Text: non-English | Not measured | 1310 | Only Qwen-Plus measured |
| LMArena Text: Chinese | Not measured | 1347 | Only Qwen-Plus measured |
| LMArena Text: Japanese | Not measured | 1251 | Only Qwen-Plus measured |
| LMArena Text: Russian | Not measured | 1323 | Only Qwen-Plus measured |
| LMArena Text: multi-turn | Not measured | 1336 | Only Qwen-Plus measured |
| LMArena Text: longer queries | Not measured | 1324 | Only Qwen-Plus measured |
| LMArena Text: writing and language | Not measured | 1296 | Only Qwen-Plus measured |
| LMArena Text: entertainment and media | Not measured | 1270 | Only Qwen-Plus measured |
| Neither model has a result on the other 29 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
Qwen-Plus costs less
Repository review
50K input + 3K output tokens
Qwen-Plus costs less
Agent loop
200K input + 10K output tokens
Qwen-Plus 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 0905 | Qwen-Plus |
|---|---|---|
| Maker | Moonshot AI | Qwen |
| Weights | Open weights | No public weights listed |
| Released | September 4, 2025 | February 1, 2025 |
| Context window | 262K | 1M |
| Input $/Mtok | $0.60 | $0.26 |
| Output $/Mtok | $2.50 | $0.78 |
| 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 0905 better than Qwen-Plus 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 0905 or Qwen-Plus?
Kimi K2 0905 costs $0.60 per million input tokens and $2.50 per million output tokens; Qwen-Plus costs $0.26 and $0.78. Cost per solved task is known for neither of them.
Which has the bigger context window, Kimi K2 0905 or Qwen-Plus?
Qwen-Plus, with 1M tokens against 262K.
Has any benchmark tested both Kimi K2 0905 and Qwen-Plus?
No benchmark has tested both yet. Kimi K2 0905 has results on LiveCodeBench (Artificial Analysis run), Terminal-Bench Hard (Artificial Analysis run) and WeirdML; Qwen-Plus on LMArena Text: coding, LMArena Text: software and IT and GPQA Diamond (Epoch AI run). Compare them on price and context instead. Data as of October 21, 2026.