Model comparison
GPT-5.5 vs Mellum2-12B-A2.5B-Instruct
Head-to-head evidence from 2 shared benchmark results across 1 category. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.5 #9 (Estimated); Mellum2-12B-A2.5B-Instruct unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.5 and Mellum2-12B-A2.5B-Instruct share 2 comparable benchmark results. 1 of 8 categories are comparable. 55 results are unique to GPT-5.5; 3 to Mellum2-12B-A2.5B-Instruct.
Updated July 23, 2026- Shared results
- 2
- GPT-5.5 only
- 55
- Mellum2-12B-A2.5B-Instruct only
- 3
- Comparable categories
- 1 / 8
Treat this as a split decision. GPT-5.5 makes more sense if knowledge is the priority or you need the larger 1M context window; Mellum2-12B-A2.5B-Instruct is the better fit if you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 2 shared benchmark results across 1 evidence category; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.5 and Mellum2-12B-A2.5B-Instruct finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
GPT-5.5 is the reasoning model in the pair, while Mellum2-12B-A2.5B-Instruct 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. GPT-5.5 gives you the larger context window at 1M, compared with 128K for Mellum2-12B-A2.5B-Instruct.
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 | GPT-5.5 | Δ | Mellum2-12B-A2.5B-Instruct |
|---|---|---|---|
| Knowledge | GPT-5.557.8 | Margin← 16.9 | Mellum2-12B-A2.5B-Instruct40.9 |
| Agentic | GPT-5.581.6 | MarginNo overlap | Mellum2-12B-A2.5B-InstructNot measured |
| Coding | GPT-5.558.6 | MarginNo overlap | Mellum2-12B-A2.5B-InstructNot measured |
| Reasoning | GPT-5.585.0 | MarginNo overlap | Mellum2-12B-A2.5B-InstructNot measured |
| Math | GPT-5.547.6 | MarginNo overlap | Mellum2-12B-A2.5B-InstructNot measured |
| Multimodal | GPT-5.570.4 | MarginNo overlap | Mellum2-12B-A2.5B-InstructNot measured |
| Inst. Following | GPT-5.5Not measured | MarginNo overlap | Mellum2-12B-A2.5B-Instruct75.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 93.6%B 40.9%Winner: GPT-5.5Δ 52.7GPQA: GPT-5.5 scored 93.6%; Mellum2-12B-A2.5B-Instruct scored 40.9%. GPT-5.5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.5 | Mellum2-12B-A2.5B-Instruct | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.5$5 input / $30 output | Mellum2-12B-A2.5B-InstructNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.5Not available | Mellum2-12B-A2.5B-InstructNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.5Not available | Mellum2-12B-A2.5B-InstructNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.51M | Mellum2-12B-A2.5B-Instruct128K | GPT-5.5 lists the larger context window. |
Benchmark Deep Dive
Agentic25 benchmarks
| Benchmark | GPT-5.5 | Mellum2-12B-A2.5B-Instruct | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 82% | — | Not comparable |
| CyberGymSource | 81.8% | — | Not comparable |
| BrowseCompSource | 84.4% | — | Not comparable |
| OSWorld-VerifiedSource | 78.7% | — | Not comparable |
| MCP AtlasSource | 75.3% | — | Not comparable |
| ToolathlonSource | 55.6% | — | Not comparable |
| τ²-bench resultsSource | 93.9% | — | Not comparable |
| AA Agentic IndexSource | 44.9% | — | Not comparable |
| APEX-Agents-AASource | 37.7% | — | Not comparable |
| GDPval-AASource | 49.5% | — | Not comparable |
| GDPval-AASource | 1490 | — | Not comparable |
| Gert LabsSource | 72.93% | — | Not comparable |
| ResearchClawBenchSource | 17.0% | — | Not comparable |
| OSWorld 2.0Source | 13.0% | — | Not comparable |
| JobBenchSource | 42.7% | — | Not comparable |
| ExploitGymSource | 13.4% | — | Not comparable |
| AA BriefcaseSource | 1154 | — | Not comparable |
| AA AutomationBenchSource | 42.1% | — | Not comparable |
| AA EnterpriseOps-GymSource | 46.6% | — | Not comparable |
| AA Harvey LABSource | 86.3% | — | Not comparable |
| AA ITBenchSource | 45.8% | — | Not comparable |
| AA Tau3 BankingSource | 31.3% | — | Not comparable |
| terminalBenchHardSource | 60.6% | — | Not comparable |
| aaTerminalBench21Source | 84.3% | — | Not comparable |
| BFCL v4Source | — | 44.2% | Not comparable |
Coding9 benchmarks
| Benchmark | GPT-5.5 | Mellum2-12B-A2.5B-Instruct | Result |
|---|---|---|---|
| SWE-bench ProSource | 58.6% | — | Not comparable |
| Terminal-Bench 2.0Source | 82.0% | — | Not comparable |
| Vibe Code BenchSource | 69.85% | — | Not comparable |
| React Native EvalsSource | 84.7% | — | Not comparable |
| cursorBench31Source | 59.2% | — | Not comparable |
| cursorBench32Source | 58.4% | — | Not comparable |
| AA Coding IndexSource | 74.9% | — | Not comparable |
| AA-SciCodeSource | 56.1% | — | Not comparable |
| FrontierCode 1.1 MainSource | 43.0% | — | Not comparable |
Reasoning5 benchmarks
KnowledgeGPT-5.5 wins11 benchmarks
| Benchmark | GPT-5.5 | Mellum2-12B-A2.5B-Instruct | Result |
|---|---|---|---|
| GPQASource | 93.6% | 40.9% | GPT-5.5 leads |
| GPQA-DSource | 93.6% | 40.9% | GPT-5.5 leads |
| HLESource | 52.2% | — | Not comparable |
| HLE w/o toolsSource | 41.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 54.8% | — | Not comparable |
| AA-GPQA DiamondSource | 93.5% | — | Not comparable |
| AA-HLESource | 44.3% | — | Not comparable |
| AA-Omniscience IndexSource | 20.1% | — | Not comparable |
| AA-Omniscience AccuracySource | 56.9% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 85.5% | — | Not comparable |
| MMLU-ReduxSource | — | 78.1% | Not comparable |
Math3 benchmarks
Multimodal5 benchmarks
Frequently Asked Questions (2)
Which is better, GPT-5.5 or Mellum2-12B-A2.5B-Instruct?
GPT-5.5 and Mellum2-12B-A2.5B-Instruct are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, GPT-5.5 or Mellum2-12B-A2.5B-Instruct?
GPT-5.5 has the edge for knowledge tasks in this comparison, averaging 57.8 versus 40.9. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.