Model comparison
GLM-5.2 vs Ornith-1.0-397B
Head-to-head evidence from 4 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5.2 #37 (Estimated); Ornith-1.0-397B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5.2 and Ornith-1.0-397B share 4 comparable benchmark results. 2 of 8 categories are comparable. 39 results are unique to GLM-5.2; 3 to Ornith-1.0-397B.
Updated July 23, 2026- Shared results
- 4
- GLM-5.2 only
- 39
- Ornith-1.0-397B only
- 3
- Comparable categories
- 2 / 8
Treat this as a split decision. GLM-5.2 makes more sense if agentic is the priority or you need the larger 1M context window; Ornith-1.0-397B is the better fit if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 4 shared benchmark results across 2 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GLM-5.2 and Ornith-1.0-397B 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.
GLM-5.2 is also the more expensive model on tokens at $1.40 input / $4.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ornith-1.0-397B. That is roughly Infinityx on output cost alone. GLM-5.2 gives you the larger context window at 1M, compared with 256K for Ornith-1.0-397B.
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 | GLM-5.2 | Δ | Ornith-1.0-397B |
|---|---|---|---|
| Coding | GLM-5.262.1 | Margin→ 12.5 | Ornith-1.0-397B74.6 |
| Agentic | GLM-5.281.0 | Margin← 3.5 | Ornith-1.0-397B77.5 |
| Knowledge | GLM-5.259.6 | MarginNo overlap | Ornith-1.0-397BNot measured |
| Math | GLM-5.295.9 | MarginNo overlap | Ornith-1.0-397BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 81%B 77.5%Winner: GLM-5.2Δ 3.5Terminal-Bench 2.0: GLM-5.2 scored 81%; Ornith-1.0-397B scored 77.5%. GLM-5.2 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 62.1%B 62.2%Winner: Ornith-1.0-397BΔ 0.1SWE-bench Pro: GLM-5.2 scored 62.1%; Ornith-1.0-397B scored 62.2%. Ornith-1.0-397B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5.2 | Ornith-1.0-397B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5.2$1.4 input / $4.4 output | Ornith-1.0-397B$0 input / $0 output | Ornith-1.0-397B has the lower combined listed price. |
| Generation speedtokens per second | GLM-5.2Not available | Ornith-1.0-397BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-5.2Not available | Ornith-1.0-397BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5.21M | Ornith-1.0-397B256K | GLM-5.2 lists the larger context window. |
Benchmark Deep Dive
AgenticGLM-5.2 wins18 benchmarks
| Benchmark | GLM-5.2 | Ornith-1.0-397B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 81% | 77.5% | GLM-5.2 leads |
| MCP AtlasSource | 76.8% | — | Not comparable |
| ToolathlonSource | 48.2% | — | Not comparable |
| AA Agentic IndexSource | 43.1% | — | Not comparable |
| τ²-bench resultsSource | 99.1% | — | Not comparable |
| GDPval-AASource | 50.7% | — | Not comparable |
| GDPval-AASource | 1514 | — | Not comparable |
| APEX-Agents-AASource | 33.7% | — | Not comparable |
| ResearchClawBenchSource | 20.7% | — | Not comparable |
| AA BriefcaseSource | 1260 | — | Not comparable |
| AA AutomationBenchSource | 27.8% | — | Not comparable |
| AA EnterpriseOps-GymSource | 42.7% | — | Not comparable |
| AA Harvey LABSource | 91.0% | — | Not comparable |
| AA ITBenchSource | 42.7% | — | Not comparable |
| AA Tau3 BankingSource | 26.8% | — | Not comparable |
| terminalBenchHardSource | 50.8% | — | Not comparable |
| aaTerminalBench21Source | 77.9% | — | Not comparable |
| Claw-EvalSource | — | 77.1% | Not comparable |
CodingOrnith-1.0-397B wins9 benchmarks
| Benchmark | GLM-5.2 | Ornith-1.0-397B | Result |
|---|---|---|---|
| SWE-bench ProSource | 62.1% | 62.2% | Ornith-1.0-397B leads |
| NL2RepoSource | 48.9% | 48.2% | GLM-5.2 leads |
| Terminal-Bench 2.0Source | 81.0% | 77.5% | GLM-5.2 leads |
| ProgramBenchSource | 63.7% | — | Not comparable |
| cursorBench32Source | 55.0% | — | Not comparable |
| AA Coding IndexSource | 68.8% | — | Not comparable |
| AA-SciCodeSource | 50.5% | — | Not comparable |
| SWE-bench VerifiedSource | — | 82.4% | Not comparable |
| SWE MultilingualSource | — | 78.9% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | GLM-5.2 | Ornith-1.0-397B | Result |
|---|---|---|---|
| GPQASource | 91.2% | — | Not comparable |
| GPQA-DSource | 91.2% | — | Not comparable |
| HLESource | 54.7% | — | Not comparable |
| HLE w/o toolsSource | 40.5% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 51.1% | — | Not comparable |
| AA-GPQA DiamondSource | 89.5% | — | Not comparable |
| AA-HLESource | 40.1% | — | Not comparable |
| AA-Omniscience IndexSource | 4.0% | — | Not comparable |
| AA-Omniscience AccuracySource | 25.1% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 28.1% | — | Not comparable |
| AA Openness IndexSource | 44.4% | — | Not comparable |
Math4 benchmarks
Multimodal1 benchmarks
| Benchmark | GLM-5.2 | Ornith-1.0-397B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1340 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GLM-5.2 | Ornith-1.0-397B | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.3% | — | Not comparable |
Frequently Asked Questions (3)
Which is better, GLM-5.2 or Ornith-1.0-397B?
GLM-5.2 and Ornith-1.0-397B 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 coding, GLM-5.2 or Ornith-1.0-397B?
Ornith-1.0-397B has the edge for coding in this comparison, averaging 74.6 versus 62.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GLM-5.2 or Ornith-1.0-397B?
GLM-5.2 has the edge for agentic tasks in this comparison, averaging 81 versus 77.5. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.
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