Compare / head-to-head
GPT-5.2vsPhi-4 Multimodal Instruct
GPT-5.2 and Phi-4 Multimodal Instruct do not yet share a public benchmark, so quality cannot be compared apples-to-apples. GPT-5.2 has the larger context window (400K tokens).
Benchmarks from cited public sources; pricing from official pages; status from official provider feeds.
Shared benchmarks
0
no overlap yet
Cheaper per token
—
list price, input + output
Larger context
GPT-5.2
400K tokens
Provider uptime (30d)
94.5205% · —
OpenAI · Microsoft
GPT-5.2
OpenAI · released 2025-12-11
textvision
Phi-4 Multimodal Instruct
Microsoft · released 2025-02-26
textvisionaudio
- Context
- 128K
- Max out
- 4K
- Input /1M
- —
- Output /1M
- —
- Cached /1M
- —
- Scores
- 19 · 0 core
Quality
Benchmark matrix
0 shared · 14 only GPT-5.2 · 19 only Phi-4 Multimodal Instruct| Benchmark | GPT-5.2 | Phi-4 Multimodal Instruct | Δ | Edge |
|---|---|---|---|---|
| Reported by both · 0 | ||||
| No public benchmark is reported for both models yet. | ||||
| Only GPT-5.2 reports · 14 | ||||
| SWE-bench Verified | 80% ↗ | not reported | — | — |
| GPQA Diamond | 92.4% ↗ | not reported | — | — |
| AIME 2025 | 100% ↗ | not reported | — | — |
| AIME 2026 | 98.3% ↗matharena | not reported | — | — |
| LMArena Elo | 1412.4 ↗ | not reported | — | — |
| ARC-AGI-1 (Verified) | 86.2% ↗ | not reported | — | — |
| ARC-AGI-2 (Verified) | 52.9% ↗ | not reported | — | — |
| FrontierMath Tier 4 v2 (Epoch AI run) | 31.7% ↗epoch | not reported | — | — |
| FrontierMath Tiers 1-3 v2 (Epoch AI run) | 67.4% ↗epoch | not reported | — | — |
| GDPval (wins or ties) | 70.9% ↗ | not reported | — | — |
| OTIS Mock AIME 2024-2025 (Epoch AI run) | 96.1% ↗epoch | not reported | — | — |
| SimpleQA Verified | 37.1% ↗epoch | not reported | — | — |
| SWE-Bench Pro | 55.6% ↗ | not reported | — | — |
| SWE-bench Verified (Epoch AI run) | 73.8% ↗epoch | not reported | — | — |
| Only Phi-4 Multimodal Instruct reports · 19 | ||||
| AI2D | not reported | 82.3% ↗ | — | — |
| BLINK | not reported | 61.3% ↗ | — | — |
| ChartQA | not reported | 81.4% ↗ | — | — |
| DocVQA | not reported | 93.2% ↗ | — | — |
| InfoVQA | not reported | 72.7% ↗ | — | — |
| InterGPS | not reported | 48.6% ↗ | — | — |
| MathVista testmini | not reported | 62.4% ↗ | — | — |
| MMBench (dev-en) | not reported | 86.7% ↗ | — | — |
| MMMU | not reported | 55.1% ↗ | — | — |
| MMMU-Pro (standard/vision) | not reported | 38.5% ↗ | — | — |
| OCRBench | not reported | 84.4% ↗ | — | — |
| POPE | not reported | 85.6% ↗ | — | — |
| ScienceQA Visual | not reported | 97.5% ↗ | — | — |
| Speech AI2D | not reported | 68.9% ↗ | — | — |
| Speech ChartQA | not reported | 69% ↗ | — | — |
| Speech DocVQA | not reported | 87.3% ↗ | — | — |
| Speech InfoVQA | not reported | 63.7% ↗ | — | — |
| TextVQA (val) | not reported | 75.6% ↗ | — | — |
| Video-MME (16 frames) | not reported | 55% ↗ | — | — |
Scores tagged "epoch" or "matharena" are independent runs, used only where the lab has not published its own; ⚠ marks rows MathArena flags as released after the competition. Higher is better on every row. Δ is GPT-5.2 minus Phi-4 Multimodal Instruct in the benchmark's own unit. "Not reported" means the lab has not published that figure; it is not a zero. ↗ opens the source.
Specs & pricing
Side by side
Official pricing pages and model cards| Spec | GPT-5.2 | Phi-4 Multimodal Instruct | Edge |
|---|---|---|---|
| Context window | 400K tokens | 128K tokens | GPT-5.2 |
| Max output | 128K tokens | 4K tokens | GPT-5.2 |
| Input price / 1M | $1.75 ↗ | — | — |
| Output price / 1M | $14 ↗ | — | — |
| Cached input / 1M | $0.175 ↗ | — | — |
| Input + output / 1M Lower is cheaper. List prices; batch, tool and regional fees excluded. | $15.75 | — | — |
| Modalities | text · vision | text · vision · audio | Phi-4 Multimodal Instruct |
| Released | 2025-12-11 | 2025-02-26 | — |
| Cited benchmark scores | 16 | 19 | — |
Reliability
Provider status
Last 60 days · refreshed daily on this page · live on /statusMore matchups
GPT-5.2 vs …
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Phi-4 Multimodal Instruct vs …
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Which one wins on your data?
Public benchmarks are a starting point. Run GPT-5.2 and Phi-4 Multimodal Instruct on your own prompts with Respan evals, or route to either through one gateway key with automatic failover.