Model comparison
Ling 2.6 Flash vs Ornith-1.0-397B
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
BenchAlign evidence: Ling 2.6 Flash estimated; Ornith-1.0-397B not scored. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Ling 2.6 Flash and Ornith-1.0-397B share 0 comparable benchmark results. 1 of 8 categories are comparable. 19 results are unique to Ling 2.6 Flash; 7 to Ornith-1.0-397B.
Updated July 16, 2026- Shared results
- 0
- Ling 2.6 Flash only
- 19
- Ornith-1.0-397B only
- 7
- Comparable categories
- 1 / 8
Pick Ornith-1.0-397B if you want the stronger benchmark profile. Ling 2.6 Flash only becomes the better choice if you need the larger 262K 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 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
Ornith-1.0-397B is clearly ahead on the provisional aggregate, 72 to 36. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Ornith-1.0-397B's sharpest advantage is in coding, where it averages 74.6 against 27.
Ornith-1.0-397B is the reasoning model in the pair, while Ling 2.6 Flash 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. Ling 2.6 Flash gives you the larger context window at 262K, compared with 256K for Ornith-1.0-397B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Ling 2.6 Flash | Ornith-1.0-397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Ling 2.6 FlashNot available | Ornith-1.0-397B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | Ling 2.6 Flash209.5 tok/s | Ornith-1.0-397BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Ling 2.6 Flash1.07 s | Ornith-1.0-397BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Ling 2.6 Flash262K | Ornith-1.0-397B256K | Ling 2.6 Flash lists the larger context window. |
Benchmark Deep Dive
Agentic6 benchmarks
CodingOrnith-1.0-397B wins9 benchmarks
| Benchmark | Ling 2.6 Flash | Ornith-1.0-397B | Result |
|---|---|---|---|
| SciCodeSource | 27% | — | Not comparable |
| AA Coding IndexSource | 25.3% | — | Not comparable |
| Terminal-Bench HardSource | 21.2% | — | Not comparable |
| AA-SciCodeSource | 27.1% | — | Not comparable |
| SWE-bench VerifiedSource | — | 82.4% | Not comparable |
| SWE-bench ProSource | — | 62.2% | Not comparable |
| SWE MultilingualSource | — | 78.9% | Not comparable |
| NL2RepoSource | — | 48.2% | Not comparable |
| Terminal-Bench 2.0Source | — | 77.5% | Not comparable |
Reasoning2 benchmarks
Knowledge7 benchmarks
| Benchmark | Ling 2.6 Flash | Ornith-1.0-397B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 14.1% | — | Not comparable |
| GPQASource | 59% | — | Not comparable |
| AA-GPQA DiamondSource | 59.3% | — | Not comparable |
| AA-HLESource | 6.2% | — | Not comparable |
| AA-Omniscience IndexSource | -65.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 15.4% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 95.8% | — | Not comparable |
Frequently Asked Questions (2)
Which is better, Ling 2.6 Flash or Ornith-1.0-397B?
Ornith-1.0-397B is ahead on BenchLM's provisional leaderboard, 72 to 36.
Which is better for coding, Ling 2.6 Flash or Ornith-1.0-397B?
Ornith-1.0-397B has the edge for coding in this comparison, averaging 74.6 versus 27. Ling 2.6 Flash stays close enough that the answer can still flip depending on your workload.
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