Model comparison
Inkling vs SWE-1.7
Head-to-head evidence from 2 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Inkling #17; SWE-1.7 unranked
Evidence parity. Inkling and SWE-1.7 share 2 comparable benchmark results. 1 of 8 categories are comparable. 14 results are unique to Inkling; 2 to SWE-1.7.
Updated July 15, 2026- Shared results
- 2
- Inkling only
- 14
- SWE-1.7 only
- 2
- Comparable categories
- 1 / 8
Pick SWE-1.7 if you want the stronger benchmark profile. Inkling only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 2 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
SWE-1.7 is clearly ahead on the provisional aggregate, 74 to 69. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
SWE-1.7's sharpest advantage is in agentic, where it averages 81.5 against 69.4. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 63.8% to 81.5%.
SWE-1.7 is the reasoning model in the pair, while Inkling is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Inkling gives you the larger context window at 1M, compared with 256K for SWE-1.7.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Inkling | Δ | SWE-1.7 |
|---|---|---|---|
| Agentic | Inkling69.4 | Margin→ 12.1 | SWE-1.781.5 |
| Coding | Inkling68.6 | MarginNo overlap | SWE-1.7Not measured |
| Knowledge | Inkling51.7 | MarginNo overlap | SWE-1.7Not measured |
| Math | Inkling97.1 | MarginNo overlap | SWE-1.7Not measured |
| Multimodal | Inkling76.5 | MarginNo overlap | SWE-1.7Not measured |
| Inst. Following | Inkling79.8 | MarginNo overlap | SWE-1.7Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 63.8%B 81.5%Winner: SWE-1.7Δ 17.7Terminal-Bench 2.0: Inkling scored 63.8%; SWE-1.7 scored 81.5%. SWE-1.7 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Inkling | SWE-1.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Inkling$1.87 input / $4.68 output | SWE-1.7Not available | A complete price comparison is not available. |
| Generation speedtokens per second | InklingNot available | SWE-1.7Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | InklingNot available | SWE-1.7Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Inkling1M | SWE-1.7256K | Inkling lists the larger context window. |
Benchmark Deep Dive
Frequently Asked Questions (2)
Which is better, Inkling or SWE-1.7?
SWE-1.7 is ahead on BenchLM's provisional leaderboard, 74 to 69. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 63.8% and 81.5%.
Which is better for agentic tasks, Inkling or SWE-1.7?
SWE-1.7 has the edge for agentic tasks in this comparison, averaging 81.5 versus 69.4. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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