Model comparison
Inkling-Small vs Qwen3-30B-A3B
Inkling-Small is the stronger model overall, scoring 46.5 to 38.5 on the Noometry Index. Qwen3-30B-A3B costs 3.0× less per token, which makes it the better buy when Inkling-Small's lead doesn't matter for your workload.
Last verified . 23 shared benchmarks.
Summary
- They share 23 benchmarks with published results for both. Inkling-Small scores higher in 8 categories and Qwen3-30B-A3B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Inkling-Small leads 39.0 to 21.6.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 90% for Inkling-Small and 70.3% for Qwen3-30B-A3B.
- Qwen3-30B-A3B is cheaper at $0.12 / $0.50 per million input/output tokens, against $0.45 / $1.20 for Inkling-Small.
- Inkling-Small accepts more context: 524K tokens versus 41K.
Side by side
| Inkling-Small | Qwen3-30B-A3B | |
|---|---|---|
| Provider | Thinking Machines Lab | Alibaba (Qwen) |
| Noometry Index | 46.5 | 38.5 |
| Released | 2026-07-15 | 2025-04-28 |
| Weights | Open | Open |
| Context window | 524K | 41K |
| Max output | 1.05M | 16K |
| Input $ / M tokens | $0.45 | $0.12 |
| Output $ / M tokens | $1.20 | $0.50 |
| Results tracked | 33 | 32 |
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Category by category
Coding Inkling-Small leads
Inkling-Small: 43.3 (#80), Qwen3-30B-A3B: 37.0 (#188)
| Benchmark | Inkling-Small | Qwen3-30B-A3B |
|---|---|---|
| SciCode | 48.7% | 33.3% |
| LMArena Coding | 1451 | 1416 |
| LMArena WebDev | 1408 | — |
| WeirdML | — | 29.8% |
Agentic & Tool Use Not comparable
Inkling-Small: —, Qwen3-30B-A3B: 29.5 (#75)
| Benchmark | Inkling-Small | Qwen3-30B-A3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 41.4% |
Reasoning Inkling-Small leads
Inkling-Small: 39.0 (#53), Qwen3-30B-A3B: 21.6 (#193)
| Benchmark | Inkling-Small | Qwen3-30B-A3B |
|---|---|---|
| CritPt | 8.3% | 0.3% |
| Chess Puzzles | 18% | 8% |
| LMArena Hard Prompts | 1424 | 1398 |
| Epoch Capabilities Index | 150.13 | 139.63 |
| ARC-AGI-2 | 40.1% | — |
| Kagi LLM Benchmark | — | 54.9% |
| ARC-AGI-1 | 84% | — |
| Mystery Game Puzzles | 6% | — |
| DTBench | — | 69.3% |
| LMCA | — | 22.4% |
Math Inkling-Small leads
Inkling-Small: 44.9 (#65), Qwen3-30B-A3B: 36.0 (#133)
| Benchmark | Inkling-Small | Qwen3-30B-A3B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 90% | 70.3% |
| LMArena Math | 1453 | 1394 |
| FrontierMath (Tiers 1-3) | 46.3% | — |
| FrontierMath Tier 4 | 17.1% | — |
| MathArena Final-Answer Competitions | — | 47.8% |
| ProofBench | 6% | — |
Knowledge Inkling-Small leads
Inkling-Small: 48.3 (#71), Qwen3-30B-A3B: 41.7 (#96)
| Benchmark | Inkling-Small | Qwen3-30B-A3B |
|---|---|---|
| GPQA Diamond | 88.5% | 70.1% |
| LMArena Expert | 1442 | 1395 |
| SimpleQA Verified | 19.1% | — |
| Confabulations | — | 12.3% |
Multimodal Not comparable
Inkling-Small: 38.4 (#59), Qwen3-30B-A3B: —
| Benchmark | Inkling-Small | Qwen3-30B-A3B |
|---|---|---|
| LMArena Vision | 1235 | — |
Multilingual Inkling-Small leads
Inkling-Small: 51.7 (#102), Qwen3-30B-A3B: 49.8 (#126)
| Benchmark | Inkling-Small | Qwen3-30B-A3B |
|---|---|---|
| LMArena Non-English | 1400 | 1372 |
| LMArena Chinese | 1458 | 1434 |
| LMArena French | 1438 | 1419 |
| LMArena German | 1412 | 1379 |
| LMArena Japanese | 1399 | 1338 |
| LMArena Korean | 1355 | 1333 |
| LMArena Russian | 1392 | 1369 |
| LMArena Spanish | 1426 | 1403 |
Instruction Following Inkling-Small leads
Inkling-Small: 73.9 (#112), Qwen3-30B-A3B: 72.2 (#137)
| Benchmark | Inkling-Small | Qwen3-30B-A3B |
|---|---|---|
| LMArena Instruction Following | 1397 | 1364 |
Long Context Inkling-Small leads
Inkling-Small: 42.7 (#113), Qwen3-30B-A3B: 31.0 (#278)
| Benchmark | Inkling-Small | Qwen3-30B-A3B |
|---|---|---|
| LMArena Longer Query | 1401 | 1379 |
| Fiction.LiveBench | — | 40.6% |
Writing & Preference Inkling-Small leads
Inkling-Small: 59.8 (#102), Qwen3-30B-A3B: 55.9 (#138)
| Benchmark | Inkling-Small | Qwen3-30B-A3B |
|---|---|---|
| LMArena Text | 1413 | 1384 |
| LMArena Creative Writing | 1330 | 1318 |
| LMArena Multi-Turn | 1420 | 1378 |
| Short-Story Creative Writing | — | 75.3% |
| EQ-Bench Creative Writing | 1491 | — |
Frequently asked questions
Is Inkling-Small better than Qwen3-30B-A3B?
Inkling-Small is the stronger model overall, scoring 46.5 to 38.5 on the Noometry Index. Qwen3-30B-A3B costs 3.0× less per token, which makes it the better buy when Inkling-Small's lead doesn't matter for your workload.
Which is cheaper, Inkling-Small or Qwen3-30B-A3B?
Qwen3-30B-A3B is cheaper. It lists at $0.12 per million input tokens and $0.50 per million output tokens; Inkling-Small lists at $0.45 and $1.20.
Is Inkling-Small or Qwen3-30B-A3B better for coding?
Inkling-Small scores higher on coding benchmarks: 43.3 versus 37.0 in the Noometry coding category.
Which has the bigger context window?
Inkling-Small does, with 524K tokens against 41K.
How many benchmarks do Inkling-Small and Qwen3-30B-A3B share?
23 benchmarks have published results for both models. Inkling-Small has 33 scored results on Noometry and Qwen3-30B-A3B has 32.