Kimi K2 Thinking vs Qwen2.5 VL 72B Instruct
Qwen2.5 VL 72B Instruct costs 2.5x less per output token than Kimi K2 Thinking ($1.00 vs $2.50 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $2.50
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.00
Kimi K2 Thinking or Qwen2.5 VL 72B Instruct: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Kimi K2 Thinking for a larger context window (262K against 128K tokens).
No benchmark has tested both yet. Kimi K2 Thinking has results on SWE-bench Verified, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI); Qwen2.5 VL 72B Instruct on OSWorld, Kagi LLM Benchmark and GeoBench. 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 Thinking has a AA Intelligence Index result, 22.0.
Directional only
Reasoning
GPQA Diamond
No call
Only Kimi K2 Thinking has a GPQA Diamond result, 78.5%.
Directional only
Math
AIME
No call
Only Kimi K2 Thinking has a AIME result, 85.4%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2 Thinking has a MMLU Pro result, 81.1%.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2 Thinking has a Design Arena: websites result, 1113.
Directional only
Long documents
Listed context window
Kimi K2 Thinking
Kimi K2 Thinking takes 262K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 VL 72B Instruct
Kimi K2 Thinking $0.0019, Qwen2.5 VL 72B Instruct $0.0013 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Kimi K2 Thinking has the number, $0.61.
Directional only
At a glance
- Coding index
- Kimi K2 Thinking not benchmarked, Qwen2.5 VL 72B 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 Thinking $2.50 against Qwen2.5 VL 72B Instruct $1.00 per million output tokens, 2.5x apart.
- Context window
- Kimi K2 Thinking takes 262K tokens, Qwen2.5 VL 72B Instruct 128K.
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 Thinking | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| SWE-bench Verified | 63.4% | Not measured | Only Kimi K2 Thinking measured |
| LiveCodeBench (Vals AI) | 63.1% | Not measured | Only Kimi K2 Thinking measured |
| SWE-bench Verified (Vals AI) | 60.2% | Not measured | Only Kimi K2 Thinking measured |
| LiveCodeBench (Artificial Analysis run) | 85.3% | Not measured | Only Kimi K2 Thinking measured |
| Terminal-Bench Hard (Artificial Analysis run) | 31.1% | Not measured | Only Kimi K2 Thinking measured |
| Terminal-Bench | 35.7% | Not measured | Only Kimi K2 Thinking measured |
| WeirdML | 42.8% | Not measured | Only Kimi K2 Thinking measured |
| ALE-Bench | 597.5 | Not measured | Only Kimi K2 Thinking 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 Thinking | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.0 | Not measured | Only Kimi K2 Thinking measured |
| Epoch Capabilities Index | 145.8 | Not measured | Only Kimi K2 Thinking measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Kimi K2 Thinking | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 93.0% | Not measured | Only Kimi K2 Thinking measured |
| METR time horizons | 59.2% | Not measured | Only Kimi K2 Thinking measured |
| OSWorld | Not measured | 5.0% | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Kimi K2 Thinking | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| GPQA Diamond | 78.5% | Not measured | Only Kimi K2 Thinking measured |
| GPQA Diamond (Artificial Analysis run) | 83.8% | Not measured | Only Kimi K2 Thinking measured |
| Humanity's Last Exam (Artificial Analysis run) | 23.8% | Not measured | Only Kimi K2 Thinking measured |
| Kagi LLM Benchmark | Not measured | 36.0% | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 18 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | Kimi K2 Thinking | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| AIME | 85.4% | Not measured | Only Kimi K2 Thinking measured |
| MGSM (Vals AI) | 90.2% | Not measured | Only Kimi K2 Thinking measured |
| AA Math Index | 94.7 | Not measured | Only Kimi K2 Thinking measured |
| AIME 2025 (Artificial Analysis run) | 94.7% | Not measured | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | Kimi K2 Thinking | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| MMLU Pro | 81.1% | Not measured | Only Kimi K2 Thinking measured |
| LegalBench (Vals AI) | 80.2% | Not measured | Only Kimi K2 Thinking measured |
| CaseLaw (Vals AI) | 65.7% | Not measured | Only Kimi K2 Thinking measured |
| CorpFin (Vals AI) | 60.6% | Not measured | Only Kimi K2 Thinking measured |
| TaxEval (Vals AI) | 71.7% | Not measured | Only Kimi K2 Thinking measured |
| MedQA (Vals AI) | 92.6% | Not measured | Only Kimi K2 Thinking measured |
| MMLU Pro (Artificial Analysis run) | 84.8% | Not measured | Only Kimi K2 Thinking measured |
| GeoBench | Not measured | 62.0% | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Kimi K2 Thinking | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| Design Arena: websites | 1113 | Not measured | Only Kimi K2 Thinking measured |
| Neither model has a result on the other 8 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | Kimi K2 Thinking | Qwen2.5 VL 72B Instruct | Leader |
|---|---|---|---|
| IFBench | 68.1% | Not measured | Only Kimi K2 Thinking measured |
| Long context reasoning (AA-LCR) | 72.0% | Not measured | Only Kimi K2 Thinking measured |
| CL-bench | 17.6% | Not measured | Only Kimi K2 Thinking measured |
| LMArena Vision | Not measured | 1107 | Only Qwen2.5 VL 72B Instruct measured |
| LMArena Vision: English | Not measured | 1115 | Only Qwen2.5 VL 72B Instruct measured |
| LMArena Vision: Chinese | Not measured | 1107 | Only Qwen2.5 VL 72B Instruct measured |
| Neither model has a result on the other 40 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
Qwen2.5 VL 72B Instruct costs less
Repository review
50K input + 3K output tokens
Kimi K2 Thinking costs less
Agent loop
200K input + 10K output tokens
Kimi K2 Thinking 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 Thinking | Qwen2.5 VL 72B Instruct |
|---|---|---|
| Maker | Moonshot AI | Qwen |
| Weights | Open weights | Open weights |
| Released | November 6, 2025 | February 1, 2025 |
| Context window | 262K | 128K |
| Input $/Mtok | $0.60 | $0.80 |
| Output $/Mtok | $2.50 | $1.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | $0.61 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2 Thinking better than Qwen2.5 VL 72B Instruct for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Kimi K2 Thinking for a larger context window (262K against 128K tokens).
Which is cheaper, Kimi K2 Thinking or Qwen2.5 VL 72B Instruct?
Kimi K2 Thinking costs $0.60 per million input tokens and $2.50 per million output tokens; Qwen2.5 VL 72B Instruct costs $0.80 and $1.00. Cost per solved task is known for Kimi K2 Thinking only.
Which has the bigger context window, Kimi K2 Thinking or Qwen2.5 VL 72B Instruct?
Kimi K2 Thinking, with 262K tokens against 128K.
Has any benchmark tested both Kimi K2 Thinking and Qwen2.5 VL 72B Instruct?
No benchmark has tested both yet. Kimi K2 Thinking has results on SWE-bench Verified, LiveCodeBench (Vals AI) and SWE-bench Verified (Vals AI); Qwen2.5 VL 72B Instruct on OSWorld, Kagi LLM Benchmark and GeoBench. Compare them on price and context instead. Data as of October 21, 2026.