Intelligence
26.3
26
General reasoning and benchmark headroom.
LimitedOpenAI: GPT-4.1 is a mid-range multimodal generalist from openai with a fast runtime profile, large context posture, and the clearest fit around long-context research / multimodal.
Benchmark blend
Dev workflow signal
Large
Mid-range tier
OpenAI: GPT-4.1 currently reads as a mid-range multimodal option with large context and a fast runtime profile.
Decision Strip
Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.
General reasoning and benchmark headroom.
LimitedTTFT 0.59s
CompetitiveHow much prompt and task state can stay in view.
Above average$8.00 output / 1M
CompetitiveEditorial Profile
Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.
GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and GPT-4.5 across coding (54.6% SWE-bench Verified), instruction compliance (87.4% IFEval), and multimodal understanding benchmarks. It is tuned for precise code diffs, agent reliability, and high recall in large document contexts, making it ideal for agents, IDE tooling, and enterprise knowledge retrieval.
openai multimodal profile
Long-context research / Multimodal with large context and fast runtime.
Balanced spend profile. Easier to justify in mixed production and exploration workloads.
Large context headroom supports repo-wide prompts and long research sessions.
Vision-capable routing opens up multimodal review and extraction workflows.
Latency and throughput look responsive enough for interactive loops.
Costs look manageable, but still deserve attention in always-on agents or batch jobs.
Image-grounded review, multimodal extraction, and UI audit workflows.
Long-context summarization, repo analysis, and policy or document review.
Benchmarks
Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.
Broad reasoning, knowledge depth, and flagship benchmark posture.
Software implementation, debugging quality, and coding benchmark signal.
Formal reasoning, structured problem solving, and competition-style math.
Long-horizon execution quality and interactive benchmark evidence.
Specs & Pricing
Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.
This model sits in a balanced spend range. It is easier to justify across both production and exploratory workflows.
Metadata
Verification details remain available, but the page no longer forces them ahead of the editorial read.