Model comparison
GLM-5 vs Nemotron 3 Super 100B
Head-to-head evidence from 1 shared benchmark result across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5 #28 (Supported); Nemotron 3 Super 100B #117 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5 and Nemotron 3 Super 100B share 1 comparable benchmark result. 0 of 8 categories are comparable. 48 results are unique to GLM-5; 0 to Nemotron 3 Super 100B.
Updated July 22, 2026- Shared results
- 1
- GLM-5 only
- 48
- Nemotron 3 Super 100B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for GLM-5 and Nemotron 3 Super 100B is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 1 shared benchmark result across 1 evidence category; 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 Super 100B. Nemotron 3 Super 100B has the larger context window at 1M, compared with 200K for GLM-5.
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 Super 100B |
|---|---|---|---|
| Agentic | GLM-556.2 | MarginNo overlap | Nemotron 3 Super 100BNot measured |
| Coding | GLM-566.3 | MarginNo overlap | Nemotron 3 Super 100BNot measured |
| Reasoning | GLM-560.8 | MarginNo overlap | Nemotron 3 Super 100BNot measured |
| Knowledge | GLM-566.4 | MarginNo overlap | Nemotron 3 Super 100BNot measured |
| Math | GLM-556.3 | MarginNo overlap | Nemotron 3 Super 100BNot measured |
| Multilingual | GLM-583.1 | MarginNo overlap | Nemotron 3 Super 100BNot measured |
| Inst. Following | GLM-592.6 | MarginNo overlap | Nemotron 3 Super 100BNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5 | Nemotron 3 Super 100B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5$1 input / $3.2 output | Nemotron 3 Super 100B$0 input / $0 output | Nemotron 3 Super 100B has the lower combined listed price. |
| Generation speedtokens per second | GLM-574 tok/s | Nemotron 3 Super 100B367 tok/s | Nemotron 3 Super 100B has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-51.64 s | Nemotron 3 Super 100B0.71 s | Nemotron 3 Super 100B reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-5200K | Nemotron 3 Super 100B1M | Nemotron 3 Super 100B lists the larger context window. |
Benchmark Deep Dive
Agentic13 benchmarks
| Benchmark | GLM-5 | Nemotron 3 Super 100B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 56.2% | — | Not comparable |
| Claw-EvalSource | 57.7% | 5.5% | GLM-5 leads |
| 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% | — | Not comparable |
| CyberGymSource | 43.2% | — | Not comparable |
| APEX-Agents-AASource | 14.5% | — | Not comparable |
| Gert LabsSource | 50.99% | — | Not comparable |
Coding7 benchmarks
| Benchmark | GLM-5 | Nemotron 3 Super 100B | 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% | — | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | GLM-5 | Nemotron 3 Super 100B | 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% | — | Not comparable |
| AA-GPQA DiamondSource | 82.0% | — | Not comparable |
| AA-HLESource | 27.2% | — | Not comparable |
| AA-Omniscience IndexSource | 2.0% | — | Not comparable |
| AA-Omniscience AccuracySource | 26.9% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 34.0% | — | Not comparable |
Math8 benchmarks
| Benchmark | GLM-5 | Nemotron 3 Super 100B | 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 Super 100B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1278 | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GLM-5 and Nemotron 3 Super 100B 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 Super 100B today?
GLM-5: $1.00 input / $3.20 output per 1M tokens Nemotron 3 Super 100B: $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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