Model comparison
GLM-4.7-Flash vs GPT-4.1 nano
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: GLM-4.7-Flash #112 (Supported); GPT-4.1 nano #170 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7-Flash and GPT-4.1 nano share 0 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to GLM-4.7-Flash; 21 to GPT-4.1 nano.
Updated July 24, 2026- Shared results
- 0
- GLM-4.7-Flash only
- 0
- GPT-4.1 nano only
- 21
- Comparable categories
- 0 / 8
Benchmark data for GLM-4.7-Flash and GPT-4.1 nano is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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 does not have sourced benchmark coverage for GLM-4.7-Flash yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
GPT-4.1 nano is priced at $0.10 input / $0.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7-Flash. GPT-4.1 nano has the larger context window at 1M, compared with 200K for GLM-4.7-Flash.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7-Flash | GPT-4.1 nano | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7-Flash$0 input / $0 output | GPT-4.1 nano$0.1 input / $0.4 output | GLM-4.7-Flash has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.7-Flash95 tok/s | GPT-4.1 nano181 tok/s | GPT-4.1 nano has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-4.7-Flash0.91 s | GPT-4.1 nano0.63 s | GPT-4.1 nano reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-4.7-Flash200K | GPT-4.1 nano1M | GPT-4.1 nano lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding2 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | GLM-4.7-Flash | GPT-4.1 nano | Result |
|---|---|---|---|
| MMLUSource | — | 80.1% | Not comparable |
| GPQASource | — | 50.3% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 9.6% | Not comparable |
| AA-GPQA DiamondSource | — | 51.2% | Not comparable |
| AA-HLESource | — | 3.9% | Not comparable |
| AA-Omniscience IndexSource | — | -56.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 13.3% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 80.4% | Not comparable |
Math1 benchmarks
| Benchmark | GLM-4.7-Flash | GPT-4.1 nano | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | — | 1.034% | Not comparable |
Multimodal2 benchmarks
Frequently Asked Questions (3)
Can I compare GLM-4.7-Flash and GPT-4.1 nano 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-4.7-Flash and GPT-4.1 nano today?
GLM-4.7-Flash: $0.00 input / $0.00 output per 1M tokens GPT-4.1 nano: $0.10 input / $0.40 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.