Model comparison
gpt-oss-20b vs Inkling-Small
Inkling-Small is the stronger model overall, scoring 46.5 to 32.5 on the Noometry Index. gpt-oss-20b costs 18× 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. gpt-oss-20b scores higher in 0 categories and Inkling-Small in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Inkling-Small leads 59.6 to 35.5.
- The biggest single-benchmark swing is GPQA Diamond: 60.8% for gpt-oss-20b and 88.5% for Inkling-Small.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.45 / $1.20 for Inkling-Small.
- Inkling-Small accepts more context: 524K tokens versus 131K.
Side by side
| gpt-oss-20b | Inkling-Small | |
|---|---|---|
| Provider | OpenAI | Thinking Machines Lab |
| Noometry Index | 32.5 | 46.5 |
| Released | 2025-08-05 | 2026-07-15 |
| Weights | Open | Open |
| Context window | 131K | 524K |
| Max output | 16K | 1.05M |
| Input $ / M tokens | $0.018 | $0.45 |
| Output $ / M tokens | $0.09 | $1.20 |
| Results tracked | 34 | 33 |
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Category by category
Coding Inkling-Small leads
gpt-oss-20b: 37.6 (#192), Inkling-Small: 43.6 (#85)
| Benchmark | gpt-oss-20b | Inkling-Small |
|---|---|---|
| SciCode | 34.4% | 48.7% |
| LMArena Coding | 1306 | 1451 |
| LMArena WebDev | — | 1409 |
| WeirdML | 40.9% | — |
| ALE-Bench | 566.05 | — |
Agentic & Tool Use Not comparable
gpt-oss-20b: 9.3 (#154), Inkling-Small: —
| Benchmark | gpt-oss-20b | Inkling-Small |
|---|---|---|
| Terminal-Bench | 3.4% | — |
Reasoning Inkling-Small leads
gpt-oss-20b: 19.3 (#261), Inkling-Small: 38.6 (#63)
| Benchmark | gpt-oss-20b | Inkling-Small |
|---|---|---|
| CritPt | 1.4% | 8.3% |
| Chess Puzzles | 4% | 18% |
| LMArena Hard Prompts | 1274 | 1423 |
| Epoch Capabilities Index | 137.82 | 150.15 |
| ARC-AGI-2 | — | 40.1% |
| Kagi LLM Benchmark | 53.2% | — |
| ARC-AGI-1 | — | 84% |
| Mystery Game Puzzles | — | 6% |
| DTBench | 68% | — |
| LMCA | 14.5% | — |
Math Inkling-Small leads
gpt-oss-20b: 39.4 (#103), Inkling-Small: 45.1 (#77)
| Benchmark | gpt-oss-20b | Inkling-Small |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 65.3% | 90% |
| LMArena Math | 1317 | 1459 |
| FrontierMath (Tiers 1-3) | — | 46.3% |
| FrontierMath Tier 4 | — | 17.1% |
| ProofBench | — | 6% |
| Omni-MATH | 56.5% | — |
Knowledge Inkling-Small leads
gpt-oss-20b: 34.6 (#195), Inkling-Small: 48.2 (#77)
| Benchmark | gpt-oss-20b | Inkling-Small |
|---|---|---|
| GPQA Diamond | 60.8% | 88.5% |
| LMArena Expert | 1258 | 1442 |
| SimpleQA Verified | — | 19.1% |
| MMLU-Pro | 74% | — |
| GPQA (HELM) | 59.4% | — |
Multimodal Not comparable
gpt-oss-20b: —, Inkling-Small: 39.1 (#62)
| Benchmark | gpt-oss-20b | Inkling-Small |
|---|---|---|
| LMArena Vision | — | 1235 |
Multilingual Inkling-Small leads
gpt-oss-20b: 42.2 (#197), Inkling-Small: 51.7 (#104)
| Benchmark | gpt-oss-20b | Inkling-Small |
|---|---|---|
| LMArena Non-English | 1268 | 1402 |
| LMArena Chinese | 1314 | 1465 |
| LMArena German | 1255 | 1405 |
| LMArena Japanese | 1244 | 1405 |
| LMArena Korean | 1236 | 1363 |
| LMArena Russian | 1278 | 1391 |
| LMArena Spanish | 1267 | 1428 |
| LMArena French | — | 1436 |
Instruction Following Inkling-Small leads
gpt-oss-20b: 61.8 (#240), Inkling-Small: 73.8 (#114)
| Benchmark | gpt-oss-20b | Inkling-Small |
|---|---|---|
| LMArena Instruction Following | 1236 | 1399 |
| IFEval | 73.2% | — |
Long Context Inkling-Small leads
gpt-oss-20b: 37.9 (#209), Inkling-Small: 42.7 (#118)
| Benchmark | gpt-oss-20b | Inkling-Small |
|---|---|---|
| LMArena Longer Query | 1250 | 1401 |
Writing & Preference Inkling-Small leads
gpt-oss-20b: 35.5 (#265), Inkling-Small: 59.6 (#107)
| Benchmark | gpt-oss-20b | Inkling-Small |
|---|---|---|
| LMArena Text | 1287 | 1414 |
| LMArena Creative Writing | 1201 | 1331 |
| EQ-Bench Creative Writing | 666 | 1491 |
| LMArena Multi-Turn | 1268 | 1418 |
| WildBench | 73.7% | — |
Frequently asked questions
Is gpt-oss-20b better than Inkling-Small?
Inkling-Small is the stronger model overall, scoring 46.5 to 32.5 on the Noometry Index. gpt-oss-20b costs 18× less per token, which makes it the better buy when Inkling-Small's lead doesn't matter for your workload.
Which is cheaper, gpt-oss-20b or Inkling-Small?
gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; Inkling-Small lists at $0.45 and $1.20.
Is gpt-oss-20b or Inkling-Small better for coding?
Inkling-Small scores higher on coding benchmarks: 43.6 versus 37.6 in the Noometry coding category.
Which has the bigger context window?
Inkling-Small does, with 524K tokens against 131K.
How many benchmarks do gpt-oss-20b and Inkling-Small share?
23 benchmarks have published results for both models. gpt-oss-20b has 34 scored results on Noometry and Inkling-Small has 33.