Holo3-122B-A10B vs SWE-1.7
Head-to-head comparison across 1benchmark categories. Overall scores shown here use BenchLM's provisional ranking lane.
Verdict
SWE-1.7 leads for most workloads.
Based on BenchLM composite scores, July 2026.
Holo3-122B-A10B
72
SWE-1.7
75
Pick SWE-1.7 if you want the stronger benchmark profile. Holo3-122B-A10B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Category Breakdown
| Benchmark | Holo3-122B-A10B | Δ | SWE-1.7 |
|---|---|---|---|
| Agentic | 78.9 | → 2.6 | 81.5 |
Operational Comparison
Holo3-122B-A10B
SWE-1.7
$0.4 / $3
N/A
N/A
N/A
N/A
N/A
64K
256K
Quick Verdict
Pick SWE-1.7 if you want the stronger benchmark profile. Holo3-122B-A10B only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
SWE-1.7 has the cleaner provisional overall profile here, landing at 75 versus 72. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
SWE-1.7's sharpest advantage is in agentic, where it averages 81.5 against 78.9.
SWE-1.7 is the reasoning model in the pair, while Holo3-122B-A10B 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. SWE-1.7 gives you the larger context window at 256K, compared with 64K for Holo3-122B-A10B.
Benchmark Deep Dive
Frequently Asked Questions (2)
Which is better, Holo3-122B-A10B or SWE-1.7?
SWE-1.7 is ahead on BenchLM's provisional leaderboard, 75 to 72.
Which is better for agentic tasks, Holo3-122B-A10B or SWE-1.7?
SWE-1.7 has the edge for agentic tasks in this comparison, averaging 81.5 versus 78.9. Holo3-122B-A10B stays close enough that the answer can still flip depending on your workload.
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