Model comparison
GLM-4.7-Flash vs Inkling-Small
Inkling-Small is the stronger model overall, scoring 46.5 to 38.4 on the Noometry Index. GLM-4.7-Flash costs 4.4× less per token, which makes it the better buy when Inkling-Small's lead doesn't matter for your workload.
Last verified . 20 shared benchmarks.
Summary
- They share 20 benchmarks with published results for both. GLM-4.7-Flash scores higher in 0 categories and Inkling-Small in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Inkling-Small leads 39.0 to 20.2.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 90% for Inkling-Small.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.45 / $1.20 for Inkling-Small.
- Inkling-Small accepts more context: 524K tokens versus 200K.
Side by side
| GLM-4.7-Flash | Inkling-Small | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Thinking Machines Lab |
| Noometry Index | 38.4 | 46.5 |
| Released | 2026-01-19 | 2026-07-15 |
| Weights | Open | Open |
| Context window | 200K | 524K |
| Max output | 131K | 1.05M |
| Input $ / M tokens | $0.06 | $0.45 |
| Output $ / M tokens | $0.40 | $1.20 |
| Results tracked | 21 | 33 |
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Category by category
Coding Inkling-Small leads
GLM-4.7-Flash: 40.0 (#133), Inkling-Small: 43.3 (#80)
| Benchmark | GLM-4.7-Flash | Inkling-Small |
|---|---|---|
| LMArena Coding | 1383 | 1451 |
| LMArena WebDev | — | 1408 |
| SciCode | — | 48.7% |
Reasoning Inkling-Small leads
GLM-4.7-Flash: 20.2 (#224), Inkling-Small: 39.0 (#53)
| Benchmark | GLM-4.7-Flash | Inkling-Small |
|---|---|---|
| Chess Puzzles | 0% | 18% |
| LMArena Hard Prompts | 1356 | 1424 |
| ARC-AGI-2 | — | 40.1% |
| ARC-AGI-1 | — | 84% |
| CritPt | — | 8.3% |
| Mystery Game Puzzles | — | 6% |
| Epoch Capabilities Index | — | 150.13 |
Math Inkling-Small leads
GLM-4.7-Flash: 34.4 (#159), Inkling-Small: 44.9 (#65)
| Benchmark | GLM-4.7-Flash | Inkling-Small |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | 90% |
| LMArena Math | 1354 | 1453 |
| FrontierMath (Tiers 1-3) | — | 46.3% |
| FrontierMath Tier 4 | — | 17.1% |
| ProofBench | — | 6% |
Knowledge Inkling-Small leads
GLM-4.7-Flash: 35.4 (#177), Inkling-Small: 48.3 (#71)
| Benchmark | GLM-4.7-Flash | Inkling-Small |
|---|---|---|
| GPQA Diamond | 60.5% | 88.5% |
| LMArena Expert | 1357 | 1442 |
| SimpleQA Verified | — | 19.1% |
| Vectara Hallucination Rate | 9.3% | — |
Multimodal Not comparable
GLM-4.7-Flash: —, Inkling-Small: 38.4 (#59)
| Benchmark | GLM-4.7-Flash | Inkling-Small |
|---|---|---|
| LMArena Vision | — | 1235 |
Multilingual Inkling-Small leads
GLM-4.7-Flash: 46.8 (#152), Inkling-Small: 51.7 (#102)
| Benchmark | GLM-4.7-Flash | Inkling-Small |
|---|---|---|
| LMArena Non-English | 1331 | 1400 |
| LMArena Chinese | 1403 | 1458 |
| LMArena French | 1332 | 1438 |
| LMArena German | 1336 | 1412 |
| LMArena Korean | 1284 | 1355 |
| LMArena Russian | 1333 | 1392 |
| LMArena Spanish | 1351 | 1426 |
| LMArena Japanese | — | 1399 |
Instruction Following Inkling-Small leads
GLM-4.7-Flash: 70.3 (#162), Inkling-Small: 73.9 (#112)
| Benchmark | GLM-4.7-Flash | Inkling-Small |
|---|---|---|
| LMArena Instruction Following | 1327 | 1397 |
Long Context Inkling-Small leads
GLM-4.7-Flash: 40.9 (#143), Inkling-Small: 42.7 (#113)
| Benchmark | GLM-4.7-Flash | Inkling-Small |
|---|---|---|
| LMArena Longer Query | 1345 | 1401 |
Writing & Preference Inkling-Small leads
GLM-4.7-Flash: 47.7 (#206), Inkling-Small: 59.8 (#102)
| Benchmark | GLM-4.7-Flash | Inkling-Small |
|---|---|---|
| LMArena Text | 1351 | 1413 |
| LMArena Creative Writing | 1297 | 1330 |
| EQ-Bench Creative Writing | 1125 | 1491 |
| LMArena Multi-Turn | 1342 | 1420 |
Frequently asked questions
Is GLM-4.7-Flash better than Inkling-Small?
Inkling-Small is the stronger model overall, scoring 46.5 to 38.4 on the Noometry Index. GLM-4.7-Flash costs 4.4× less per token, which makes it the better buy when Inkling-Small's lead doesn't matter for your workload.
Which is cheaper, GLM-4.7-Flash or Inkling-Small?
GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Inkling-Small lists at $0.45 and $1.20.
Is GLM-4.7-Flash or Inkling-Small better for coding?
Inkling-Small scores higher on coding benchmarks: 43.3 versus 40.0 in the Noometry coding category.
Which has the bigger context window?
Inkling-Small does, with 524K tokens against 200K.
How many benchmarks do GLM-4.7-Flash and Inkling-Small share?
20 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Inkling-Small has 33.