Model comparison
GLM-4.7-Flash vs Llama 3.1 405B
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 #106 (Supported); Llama 3.1 405B #102 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7-Flash and Llama 3.1 405B share 0 comparable benchmark results. 0 of 8 categories are comparable. 0 results are unique to GLM-4.7-Flash; 11 to Llama 3.1 405B.
Updated July 20, 2026- Shared results
- 0
- GLM-4.7-Flash only
- 0
- Llama 3.1 405B only
- 11
- Comparable categories
- 0 / 8
Benchmark data for GLM-4.7-Flash and Llama 3.1 405B 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.
GLM-4.7-Flash has the larger context window at 200K, compared with 128K for Llama 3.1 405B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7-Flash | Llama 3.1 405B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7-Flash$0 input / $0 output | Llama 3.1 405B$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | GLM-4.7-Flash95 tok/s | Llama 3.1 405B29 tok/s | GLM-4.7-Flash has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-4.7-Flash0.91 s | Llama 3.1 405B2.19 s | GLM-4.7-Flash reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-4.7-Flash200K | Llama 3.1 405B128K | GLM-4.7-Flash lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | GLM-4.7-Flash | Llama 3.1 405B | Result |
|---|---|---|---|
| τ²-bench resultsSource | — | 19% | Not comparable |
Coding1 benchmarks
| Benchmark | GLM-4.7-Flash | Llama 3.1 405B | Result |
|---|---|---|---|
| AA-SciCodeSource | — | 29.9% | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GLM-4.7-Flash | Llama 3.1 405B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | — | 8.5% | Not comparable |
| AA-GPQA DiamondSource | — | 51.5% | Not comparable |
| AA-HLESource | — | 4.2% | Not comparable |
| AA-Omniscience IndexSource | — | -17.3% | Not comparable |
| AA-Omniscience AccuracySource | — | 22.3% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 51.0% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GLM-4.7-Flash | Llama 3.1 405B | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 39.0% | Not comparable |
Frequently Asked Questions (3)
Can I compare GLM-4.7-Flash and Llama 3.1 405B 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 Llama 3.1 405B today?
GLM-4.7-Flash: $0.00 input / $0.00 output per 1M tokens Llama 3.1 405B: $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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