Model comparison
GLM-4.7 vs Mercury 2
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: GLM-4.7 #32; Mercury 2 unranked
BenchAlign evidence: GLM-4.7 supported; Mercury 2 supported. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7 and Mercury 2 share 0 comparable benchmark results. 0 of 8 categories are comparable. 31 results are unique to GLM-4.7; 0 to Mercury 2.
Updated July 16, 2026- Shared results
- 0
- GLM-4.7 only
- 31
- Mercury 2 only
- 0
- Comparable categories
- 0 / 8
Benchmark data for GLM-4.7 and Mercury 2 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 Mercury 2 yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Mercury 2 is priced at $0.25 input / $0.75 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7. GLM-4.7 has the larger context window at 200K, compared with 128K for Mercury 2.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7 | Mercury 2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | Mercury 2$0.25 input / $0.75 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.782 tok/s | Mercury 2789 tok/s | Mercury 2 has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | Mercury 23.88 s | GLM-4.7 reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-4.7200K | Mercury 2128K | GLM-4.7 lists the larger context window. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | GLM-4.7 | Mercury 2 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 41% | — | Not comparable |
| BrowseCompSource | 52% | — | Not comparable |
| VITA-BenchSource | 15.5% | — | Not comparable |
| AA Agentic IndexSource | 25.4% | — | Not comparable |
| τ²-bench resultsSource | 95.9% | — | Not comparable |
| Gert LabsSource | 39.95% | — | Not comparable |
| GDPval-AASource | 33.3% | — | Not comparable |
| GDPval-AASource | 1165 | — | Not comparable |
Coding7 benchmarks
| Benchmark | GLM-4.7 | Mercury 2 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.8% | — | Not comparable |
| LiveCodeBenchSource | 84.9% | — | Not comparable |
| SWE-RebenchSource | 58.7% | — | Not comparable |
| AA Coding IndexSource | 45.3% | — | Not comparable |
| Terminal-Bench HardSource | 31.8% | — | Not comparable |
| AA-SciCodeSource | 45.1% | — | Not comparable |
| AA LiveCodeBenchSource | 89.4% | — | Not comparable |
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | GLM-4.7 | Mercury 2 | Result |
|---|---|---|---|
| GPQASource | 85.7% | — | Not comparable |
| MMLU-ProSource | 84.3% | — | Not comparable |
| HLESource | 24.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 33.7% | — | Not comparable |
| AA-GPQA DiamondSource | 85.9% | — | Not comparable |
| AA-HLESource | 25.1% | — | Not comparable |
| AA-Omniscience IndexSource | -34.6% | — | Not comparable |
| AA-Omniscience AccuracySource | 29.3% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 90.3% | — | Not comparable |
Math3 benchmarks
Multimodal1 benchmarks
| Benchmark | GLM-4.7 | Mercury 2 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1260 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GLM-4.7 | Mercury 2 | Result |
|---|---|---|---|
| AA-IFBenchSource | 67.9% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare GLM-4.7 and Mercury 2 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 and Mercury 2 today?
GLM-4.7: $0.00 input / $0.00 output per 1M tokens Mercury 2: $0.25 input / $0.75 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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