Model comparison
Claude Fable 5 vs GLM-5
Head-to-head evidence from 15 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Fable 5 #3 (Supported); GLM-5 #30 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Fable 5 and GLM-5 share 15 comparable benchmark results. 2 of 8 categories are comparable. 19 results are unique to Claude Fable 5; 34 to GLM-5.
Updated July 24, 2026- Shared results
- 15
- Claude Fable 5 only
- 19
- GLM-5 only
- 34
- Comparable categories
- 2 / 8
Pick Claude Fable 5 if you want the stronger benchmark profile. GLM-5 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 15 shared benchmark results across 6 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Claude Fable 5 is clearly ahead on the BenchAlign aggregate, 82.76 to 65.29. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Fable 5's sharpest advantage is in agentic, where it averages 84.6 against 56.2. The single biggest benchmark swing on the page is Terminal-Bench 2.0, 84.3% to 56.2%.
Claude Fable 5 is also the more expensive model on tokens at $10.00 input / $50.00 output per 1M tokens, versus $1.00 input / $3.20 output per 1M tokens for GLM-5. That is roughly 15.6x on output cost alone. Claude Fable 5 is the reasoning model in the pair, while GLM-5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Claude Fable 5 gives you 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 | Claude Fable 5 | Δ | GLM-5 |
|---|---|---|---|
| Agentic | Claude Fable 584.6 | Margin← 28.4 | GLM-556.2 |
| Coding | Claude Fable 589.2 | Margin← 22.9 | GLM-566.3 |
| Reasoning | Claude Fable 5Not measured | MarginNo overlap | GLM-560.8 |
| Knowledge | Claude Fable 5Not measured | MarginNo overlap | GLM-566.4 |
| Math | Claude Fable 5Not measured | MarginNo overlap | GLM-556.3 |
| Multilingual | Claude Fable 5Not measured | MarginNo overlap | GLM-583.1 |
| Multimodal | Claude Fable 557.9 | MarginNo overlap | GLM-5Not measured |
| Inst. Following | Claude Fable 5Not measured | MarginNo overlap | GLM-592.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
Terminal-Bench 2.0
AgenticA 84.3%B 56.2%Winner: Claude Fable 5Δ 28.1Terminal-Bench 2.0: Claude Fable 5 scored 84.3%; GLM-5 scored 56.2%. Claude Fable 5 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 80%B 55.1%Winner: Claude Fable 5Δ 24.9SWE-bench Pro: Claude Fable 5 scored 80%; GLM-5 scored 55.1%. Claude Fable 5 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 95%B 77.8%Winner: Claude Fable 5Δ 17.2SWE-bench Verified: Claude Fable 5 scored 95%; GLM-5 scored 77.8%. Claude Fable 5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Fable 5 | GLM-5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Fable 5$10 input / $50 output | GLM-5$1 input / $3.2 output | GLM-5 has the lower combined listed price. |
| Generation speedtokens per second | Claude Fable 5Not available | GLM-574 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Fable 5Not available | GLM-51.64 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Fable 51M+ | GLM-5200K | Claude Fable 5 lists the larger context window. |
Benchmark Deep Dive
AgenticClaude Fable 5 wins24 benchmarks
| Benchmark | Claude Fable 5 | GLM-5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 84.3% | 56.2% | Claude Fable 5 leads |
| OSWorld-VerifiedSource | 85% | — | Not comparable |
| GDPval-AASource | 1747 | — | Not comparable |
| AA Agentic IndexSource | 52.8% | — | Not comparable |
| τ²-bench resultsSource | 98.5% | 98.2% | Claude Fable 5 leads |
| GDPval-AASource | 62.3% | — | Not comparable |
| AA BriefcaseSource | 1574 | — | Not comparable |
| AA AutomationBenchSource | 48.6% | — | Not comparable |
| AA EnterpriseOps-GymSource | 51.1% | — | Not comparable |
| AA Harvey LABSource | 93.6% | — | Not comparable |
| AA Tau3 BankingSource | 26.8% | — | Not comparable |
| terminalBenchHardSource | 62.9% | — | Not comparable |
| aaTerminalBench21Source | 84.6% | — | 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 |
| CyberGymSource | — | 43.2% | Not comparable |
| APEX-Agents-AASource | — | 14.5% | Not comparable |
| Gert LabsSource | — | 50.99% | Not comparable |
CodingClaude Fable 5 wins13 benchmarks
| Benchmark | Claude Fable 5 | GLM-5 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 95% | 77.8% | Claude Fable 5 leads |
| SWE-bench ProSource | 80% | 55.1% | Claude Fable 5 leads |
| FrontierCode 1.1 MainSource | 53.5% | — | Not comparable |
| Terminal-Bench 2.0Source | 84.3% | — | Not comparable |
| cursorBench31Source | 70.6% | — | Not comparable |
| cursorBench32Source | 70.5% | — | Not comparable |
| VulcanBench v3Source | 87.0% | — | Not comparable |
| AA Coding IndexSource | 76.5% | — | Not comparable |
| AA-SciCodeSource | 60.2% | 46.2% | Claude Fable 5 leads |
| SWE-bench Verified*Source | — | 72.8% | Not comparable |
| SWE MultilingualSource | — | 73.3% | Not comparable |
| SWE-RebenchSource | — | 62.8% | Not comparable |
| React Native EvalsSource | — | 74.8% | Not comparable |
Reasoning4 benchmarks
Knowledge12 benchmarks
| Benchmark | Claude Fable 5 | GLM-5 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 59.9% | 39.5% | Claude Fable 5 leads |
| AA-GPQA DiamondSource | 92.6% | 82.0% | Claude Fable 5 leads |
| AA-HLESource | 53.3% | 27.2% | Claude Fable 5 leads |
| AA-Omniscience IndexSource | 40.2% | 2.0% | Claude Fable 5 leads |
| AA-Omniscience AccuracySource | 61.4% | 26.9% | Claude Fable 5 leads |
| AA-Omniscience Hallucination RateSource | 54.9% | 34.0% | GLM-5 leads |
| 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 |
Math8 benchmarks
| Benchmark | Claude Fable 5 | GLM-5 | 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
Multimodal3 benchmarks
Frequently Asked Questions (3)
Which is better, Claude Fable 5 or GLM-5?
Claude Fable 5 is ahead on BenchLM's BenchAlign leaderboard, 82.76 to 65.29. The biggest single separator in this matchup is Terminal-Bench 2.0, where the scores are 84.3% and 56.2%.
Which is better for coding, Claude Fable 5 or GLM-5?
Claude Fable 5 has the edge for coding in this comparison, averaging 89.2 versus 66.3. Inside this category, SWE-bench Pro is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Claude Fable 5 or GLM-5?
Claude Fable 5 has the edge for agentic tasks in this comparison, averaging 84.6 versus 56.2. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.