Grok 4.6 wins on price ($2 vs $5/1M input). GPT-5.6 Sol wins on coding (97 vs 86) and writing quality and context window (1.05M vs 500K). For most workflows, GPT-5.6 Sol is the stronger default — best openai flagship — leads terminal coding and agentic browsing.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
GPT-5.6 Sol is the safest overall answer here when you want the strongest default instead of the lowest list price.
Mistral: Mistral Nemo is the lower-cost option to start with when you still need useful output at scale.
Grok 4.6 is the better pick when response speed matters more than maximum reasoning depth.
GPT-5.6 Sol leads on coding with a score of 97 vs 86 for Grok 4.6.
GPT-5.6 Sol has the larger context window: 1.05M vs 500K for Grok 4.6.
Grok 4.6 is cheaper at $2/1M input tokens vs $5/1M for GPT-5.6 Sol.
Go with GPT-5.6 Sol if you want one model to handle coding and research — it targets frontier agentic coding, deep research, and hardest reasoning tasks.
Grok 4.6 earns its place when your work is mostly long-running agents and multi-step codebase work, even though it loses the overall count here.
Grok 4.6 is the more cost-efficient option at $2/1M input — GPT-5.6 Sol costs 3x more per input token, so the gap is worth taking seriously wherever token volume rather than peak quality drives the bill.
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
OpenAI / Premium / Aug 6, 2026
Best OpenAI flagship — leads terminal coding and agentic browsing.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
Repo-level coding is the main job — Opus 5 leads SWE-bench Pro by ~15 points — or you're cost-sensitive (Terra is 60% cheaper at 1–4 points off).
The fastest way to see where the recommendation shifts when your priority changes.
Finishes agent tasks in half the turns — cheap where it counts.
Best OpenAI flagship — leads terminal coding and agentic browsing.
Every figure below is the provider's list price or a published capability score — the same numbers the recommendation on this page is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| GPT-5.6 SolOpenAI | $5.00/1M | $30.00/1M | $110 | 1.1M tokens | Deliberate | 97 | 94 | 97 |
| Grok 4.6xAI | $2.00/1M | $6.00/1M | $32 | 500k tokens | Fast | 86 | 84 | 88 |
Capability scores are out of 100 and reflect our own weighting of published benchmarks and production signals — see how we evaluate models. “Est. month” assumes 10M input and 2M output tokens at list price, with no batch or caching discounts applied, so treat it as a ceiling.
What each one is genuinely good at, where it falls down, and the situations we would steer you away from it — not just the headline score.
The flagship of OpenAI's GPT-5.6 family — its most capable reasoning and agentic-coding model, with an 'ultra' mode that spawns sub-agents for long autonomous workflows.
Repo-level coding is the main job — Opus 5 leads SWE-bench Pro by ~15 points — or you're cost-sensitive (Terra is 60% cheaper at 1–4 points off).
OpenAI's strongest model and the terminal-workflow leader. Sol beats everything on Terminal-Bench and agentic browsing, but Claude Opus 5 remains the better pick for repository-level software engineering.
First frontier model family to clear a customer-by-customer US government review: limited preview June 26, full public release July 9, 2026. Pricing $5/$30 ($10/$45 above 272K context). Knowledge cutoff Feb 16, 2026.
xAI's long-horizon agent model — it finishes agentic tasks in roughly half the turns of its rivals, which makes it cheaper in practice than its per-token price suggests.
You need a published SWE-bench score to justify the pick, or your prompts routinely cross 200K tokens where the price doubles.
Buy it for turn efficiency, not for benchmark ceilings. On long agent runs, finishing in half the turns beats a model that scores two points higher and takes twice as many round trips.
Released August 12, 2026, succeeding Grok 4.5. Long-context billing is a cliff, not a ramp: at 200K tokens and above the whole request is charged at $4/$12. DeepSWE 65.9%, CursorBench 3.2 70.8%, FrontierCode 1.1 Extended 61.3%, Terminal-Bench 3.0 26.5%, APEX-Agents 57.5%.
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GPT-5.6 Sol wins on more of the categories we score — coding, research, reasoning — so it is the better default of the two. Grok 4.6 is the better pick when your work is mostly long-running agents and multi-step codebase work. Neither is universally "better": GPT-5.6 Sol is aimed at frontier agentic coding and deep research, Grok 4.6 at long-running agents and multi-step codebase work.
Grok 4.6 is cheaper at $2/1M input and $6/1M output. GPT-5.6 Sol costs $5/1M input and $30/1M output.
GPT-5.6 Sol has the larger context window at 1.05M tokens vs Grok 4.6's 500K. For large document analysis, GPT-5.6 Sol is the stronger pick.
GPT-5.6 Sol is better for coding with a score of 97 vs Grok 4.6's 86 (out of 100). Claude Fable 5 is the overall coding leader in this directory at 100/100.
Grok 4.6 is faster with a fast speed rating (score: 4) vs GPT-5.6 Sol's deliberate rating (score: 2). Speed matters most for interactive and high-throughput work; for batch jobs the GPT-5.6 Sol latency penalty is usually invisible.
Trails Claude Opus 5 badly on repository-level engineering (SWE-bench Pro 64.6% vs 79.2%). Long-context surcharge ($10/$45 above 272K) and 2–3x ultra-mode costs stack up fast. Avoid it if repo-level coding is the main job — Opus 5 leads SWE-bench Pro by ~15 points — or you're cost-sensitive (Terra is 60% cheaper at 1–4 points off). That is the main case for looking at Grok 4.6 instead.
No published SWE-bench Verified or SWE-bench Pro figure, so it cannot be compared directly on the standard coding leaderboard. GPT-5.6 Sol Max beats it on DeepSWE v1.1 and Terminal-Bench 3.0. Prompts of 200K tokens or more are billed at $4/$12 across the entire request, not just the overage. Avoid it if you need a published SWE-bench score to justify the pick, or your prompts routinely cross 200K tokens where the price doubles. Against GPT-5.6 Sol specifically, the gap shows up most on coding (97 vs 86).
Take a moderate workload of 10M input and 2M output tokens a month. Grok 4.6 runs $32.00 (at $2/1M in and $6/1M out); GPT-5.6 Sol runs $110.00 (at $5/1M in and $30/1M out). That is a $78.00/month difference — Grok 4.6 is the cheaper of the two at this volume, and the gap scales linearly as you send more. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is GPT-5.6 Sol for frontier agentic coding and deep research, with Grok 4.6 handling long-running agents and multi-step codebase work. Routing high-volume, low-stakes calls to Grok 4.6 at $2/1M and reserving GPT-5.6 Sol for the hard cases is usually the cheapest arrangement that does not cost you quality.