Model comparison
Holo3-122B-A10B vs Qwen3.6-27B
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Holo3-122B-A10B unranked (Not scored); Qwen3.6-27B #93 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Holo3-122B-A10B and Qwen3.6-27B share 0 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Holo3-122B-A10B; 54 to Qwen3.6-27B.
Updated July 21, 2026- Shared results
- 0
- Holo3-122B-A10B only
- 1
- Qwen3.6-27B only
- 54
- Comparable categories
- 1 / 8
Treat this as a split decision. Holo3-122B-A10B makes more sense if agentic is the priority or you would rather avoid the extra latency and token burn of a reasoning model; Qwen3.6-27B is the better fit if you want the cheaper token bill or you need the larger 262K context window.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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
Holo3-122B-A10B and Qwen3.6-27B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Holo3-122B-A10B is also the more expensive model on tokens at $0.40 input / $3.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.6-27B. That is roughly Infinityx on output cost alone. Qwen3.6-27B 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. Qwen3.6-27B gives you the larger context window at 262K, compared with 64K for Holo3-122B-A10B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Holo3-122B-A10B | Qwen3.6-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Holo3-122B-A10B$0.4 input / $3 output | Qwen3.6-27B$0 input / $0 output | Qwen3.6-27B has the lower combined listed price. |
| Generation speedtokens per second | Holo3-122B-A10BNot available | Qwen3.6-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Holo3-122B-A10BNot available | Qwen3.6-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Holo3-122B-A10B64K | Qwen3.6-27B262K | Qwen3.6-27B lists the larger context window. |
Benchmark Deep Dive
AgenticHolo3-122B-A10B wins11 benchmarks
| Benchmark | Holo3-122B-A10B | Qwen3.6-27B | Result |
|---|---|---|---|
| OSWorld-VerifiedSource | 78.8% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| Claw-EvalSource | — | 72.4% | Not comparable |
| QwenClawBenchSource | — | 53.4% | Not comparable |
| QwenWebBenchSource | — | 1487 | Not comparable |
| AndroidWorldSource | — | 70.3% | Not comparable |
| AA Agentic IndexSource | — | 27.0% | Not comparable |
| τ²-bench resultsSource | — | 94.2% | Not comparable |
| GDPval-AASource | — | 32.0% | Not comparable |
| GDPval-AASource | — | 1140 | Not comparable |
| Gert LabsSource | — | 54.84% | Not comparable |
Coding8 benchmarks
| Benchmark | Holo3-122B-A10B | Qwen3.6-27B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | — | 77.2% | Not comparable |
| SWE MultilingualSource | — | 71.3% | Not comparable |
| SWE-bench ProSource | — | 53.5% | Not comparable |
| Terminal-Bench 2.0Source | — | 59.3% | Not comparable |
| LiveCodeBenchSource | — | 83.9% | Not comparable |
| NL2RepoSource | — | 36.2% | Not comparable |
| AA Coding IndexSource | — | 53.7% | Not comparable |
| AA-SciCodeSource | — | 39.8% | Not comparable |
Reasoning2 benchmarks
Knowledge12 benchmarks
| Benchmark | Holo3-122B-A10B | Qwen3.6-27B | Result |
|---|---|---|---|
| MMLU-ProSource | — | 86.2% | Not comparable |
| MMLU-ReduxSource | — | 93.5% | Not comparable |
| SuperGPQASource | — | 66% | Not comparable |
| C-EvalSource | — | 91.4% | Not comparable |
| GPQASource | — | 87.8% | Not comparable |
| HLESource | — | 24% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 37.0% | Not comparable |
| AA-GPQA DiamondSource | — | 84.2% | Not comparable |
| AA-HLESource | — | 21.6% | Not comparable |
| AA-Omniscience IndexSource | — | -19.8% | Not comparable |
| AA-Omniscience AccuracySource | — | 19.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 48.3% | Not comparable |
Math5 benchmarks
Multimodal16 benchmarks
| Benchmark | Holo3-122B-A10B | Qwen3.6-27B | Result |
|---|---|---|---|
| MMMUSource | — | 82.9% | Not comparable |
| MMMU-ProSource | — | 75.8% | Not comparable |
| RealWorldQASource | — | 84.1% | Not comparable |
| DynaMathSource | — | 85.6% | Not comparable |
| MStarSource | — | 81.4% | Not comparable |
| SimpleVQASource | — | 56.1% | Not comparable |
| CharXivSource | — | 78.4% | Not comparable |
| CC-OCRSource | — | 81.2% | Not comparable |
| CountBenchSource | — | 97.8% | Not comparable |
| RefCOCO (avg)Source | — | 92.5% | Not comparable |
| ERQASource | — | 62.5% | Not comparable |
| Video-MME (with subtitle)Source | — | 87.7% | Not comparable |
| VideoMMMUSource | — | 84.4% | Not comparable |
| MLVU (M-Avg)Source | — | 86.6% | Not comparable |
| V*Source | — | 94.7% | Not comparable |
| AA-MMMU-ProSource | — | 74.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Holo3-122B-A10B | Qwen3.6-27B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 67.6% | Not comparable |
Frequently Asked Questions (2)
Which is better, Holo3-122B-A10B or Qwen3.6-27B?
Holo3-122B-A10B and Qwen3.6-27B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for agentic tasks, Holo3-122B-A10B or Qwen3.6-27B?
Holo3-122B-A10B has the edge for agentic tasks in this comparison, averaging 78.9 versus 59.3. Qwen3.6-27B stays close enough that the answer can still flip depending on your workload.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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