Model comparison
GLM-5 vs Nemotron 3 Nano 30B
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5 #28 (Supported); Nemotron 3 Nano 30B #98 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5 and Nemotron 3 Nano 30B share 11 comparable benchmark results. 0 of 8 categories are comparable. 38 results are unique to GLM-5; 4 to Nemotron 3 Nano 30B.
Updated July 22, 2026- Shared results
- 11
- GLM-5 only
- 38
- Nemotron 3 Nano 30B only
- 4
- Comparable categories
- 0 / 8
Benchmark data for GLM-5 and Nemotron 3 Nano 30B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
GLM-5 is priced at $1.00 input / $3.20 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Nemotron 3 Nano 30B. GLM-5 has the larger context window at 200K, compared with 32K for Nemotron 3 Nano 30B.
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 | Δ | Nemotron 3 Nano 30B |
|---|---|---|---|
| Agentic | GLM-556.2 | MarginNo overlap | Nemotron 3 Nano 30BNot measured |
| Coding | GLM-566.3 | MarginNo overlap | Nemotron 3 Nano 30BNot measured |
| Reasoning | GLM-560.8 | MarginNo overlap | Nemotron 3 Nano 30BNot measured |
| Knowledge | GLM-566.4 | MarginNo overlap | Nemotron 3 Nano 30BNot measured |
| Math | GLM-556.3 | MarginNo overlap | Nemotron 3 Nano 30BNot measured |
| Multilingual | GLM-583.1 | MarginNo overlap | Nemotron 3 Nano 30BNot measured |
| Inst. Following | GLM-592.6 | MarginNo overlap | Nemotron 3 Nano 30BNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5 | Nemotron 3 Nano 30B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5$1 input / $3.2 output | Nemotron 3 Nano 30B$0 input / $0 output | Nemotron 3 Nano 30B has the lower combined listed price. |
| Generation speedtokens per second | GLM-574 tok/s | Nemotron 3 Nano 30B152 tok/s | Nemotron 3 Nano 30B has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-51.64 s | Nemotron 3 Nano 30B1.90 s | GLM-5 reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-5200K | Nemotron 3 Nano 30B32K | GLM-5 lists the larger context window. |
Benchmark Deep Dive
Agentic16 benchmarks
| Benchmark | GLM-5 | Nemotron 3 Nano 30B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 56.2% | — | Not comparable |
| Claw-EvalSource | 57.7% | — | Not comparable |
| QwenClawBenchSource | 54.1% | — | Not comparable |
| τ³-bench resultsSource | 65.6% | — | Not comparable |
| DeepPlanningSource | 14.6% | — | Not comparable |
| ToolathlonSource | 38% | — | Not comparable |
| MCP AtlasSource | 31.1% | — | Not comparable |
| MCP-TasksSource | 60.8% | — | Not comparable |
| WideResearchSource | 69.8% | — | Not comparable |
| τ²-bench resultsSource | 98.2% | 40.9% | GLM-5 leads |
| CyberGymSource | 43.2% | — | Not comparable |
| APEX-Agents-AASource | 14.5% | — | Not comparable |
| Gert LabsSource | 50.99% | — | Not comparable |
| GDPval-AASource | — | 0.0% | Not comparable |
| GDPval-AASource | — | 484 | Not comparable |
| AA Agentic IndexSource | — | 2.0% | Not comparable |
Coding8 benchmarks
| Benchmark | GLM-5 | Nemotron 3 Nano 30B | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 77.8% | — | Not comparable |
| SWE-bench Verified*Source | 72.8% | — | Not comparable |
| SWE-bench ProSource | 55.1% | — | Not comparable |
| SWE MultilingualSource | 73.3% | — | Not comparable |
| SWE-RebenchSource | 62.8% | — | Not comparable |
| React Native EvalsSource | 74.8% | — | Not comparable |
| AA-SciCodeSource | 46.2% | 29.6% | GLM-5 leads |
| AA Coding IndexSource | — | 14.4% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | GLM-5 | Nemotron 3 Nano 30B | Result |
|---|---|---|---|
| GPQASource | 86% | — | Not comparable |
| GPQA-DSource | 86.0% | — | Not comparable |
| SuperGPQASource | 66.8% | — | Not comparable |
| MMLU-ProSource | 85.7% | — | Not comparable |
| MMLU-Pro (Arcee)Source | 85.8% | — | Not comparable |
| HLESource | 50.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 39.5% | 14.2% | GLM-5 leads |
| AA-GPQA DiamondSource | 82.0% | 75.7% | GLM-5 leads |
| AA-HLESource | 27.2% | 10.2% | GLM-5 leads |
| AA-Omniscience IndexSource | 2.0% | -51.6% | GLM-5 leads |
| AA-Omniscience AccuracySource | 26.9% | 17.1% | GLM-5 leads |
| AA-Omniscience Hallucination RateSource | 34.0% | 82.9% | GLM-5 leads |
Math8 benchmarks
| Benchmark | GLM-5 | Nemotron 3 Nano 30B | Result |
|---|---|---|---|
| AIME26Source | 95.8% | — | Not comparable |
| AIME25 (Arcee)Source | 93.3% | — | Not comparable |
| HMMT Feb 2025Source | 97.5% | — | Not comparable |
| HMMT Nov 2025Source | 96.9% | — | Not comparable |
| HMMT Feb 2026Source | 86.4% | — | Not comparable |
| MMAnswerBenchSource | 82.5% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 16.434% | — | Not comparable |
| FrontierMath v2 (Tier 4)Source | 2.100% | — | Not comparable |
Multilingual2 benchmarks
Multimodal1 benchmarks
| Benchmark | GLM-5 | Nemotron 3 Nano 30B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1278 | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GLM-5 and Nemotron 3 Nano 30B on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for GLM-5 and Nemotron 3 Nano 30B today?
GLM-5: $1.00 input / $3.20 output per 1M tokens Nemotron 3 Nano 30B: $0.00 input / $0.00 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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