Grok 4

Grok 4 is most compelling for developers who value mathematical reasoning more than broad, proven production evidence.

The available data gives Grok 4 a clear strength: it ranks 16 of 265 on the Artificial Analysis Math Index with a score of 92.7. That position makes mathematics the strongest evidence-backed reason to consider the model. Grok 4 also ranks 118 of 578 on the Artificial Analysis Intelligence Index with a score of 33.3, which places it in a much less distinctive position on the broader measure.

The pricing picture is mixed. Grok 4 costs $6 per 1M blended tokens, with input tokens priced at $3 and output tokens priced at $15. That is materially higher than the closest listed low-cost reference, GPT-5.6 Luna (low), at $0.45 per 1M blended tokens. It is lower than MiMo-V2-Flash (Feb 2026), listed at $15 per 1M blended tokens. The data therefore supports a focused purchase decision, not a general recommendation for every workload.

The research brief contains no verified official positioning, pricing source, community discussion, or documented failure analysis. Developers should treat the benchmark result as useful directional evidence, while validating reliability, tool use, coding quality, and operational fit themselves. Data provided by https://artificialanalysis.ai/

Grok 4 is a specialist-leaning option whose mathematical result is stronger than its broad intelligence ranking suggests.

For a developer choosing among nearby models, the central trade-off is straightforward. Grok 4 offers a stronger mathematics signal than Gemini 3 Pro Preview (low), which scores 86.7 on the Artificial Analysis Math Index in the supplied comparison set. Grok 4 also costs more than Gemini 3 Pro Preview (low), whose blended price is listed as $4.500000000000001 per 1M tokens. The difference is not large enough to settle the decision without workload testing.

Grok 4 looks less attractive for generic assistant traffic. Its broad intelligence score of 33.3 is close to the listed scores for GPT-5.6 Luna (low) at 33.3, MiMo-V2-Flash (Feb 2026) at 33.2, Gemini 3 Pro Preview (low) at 33.1, and GPT-5.5 Instant (May 2026) at 33.5. Those nearby results suggest that Grok 4 does not have a clear general-intelligence lead in this comparison set.

The most important unknown is real task behavior. The research brief found no reliable official source and no usable Reddit, Hacker News, or X posts. That means there is insufficient evidence to judge answer consistency, refusal behavior, coding workflows, context handling, or support quality. Developers should make those factors part of their own evaluation rather than treating the benchmark as a complete product assessment.

Decision factor	Grok 4 implication
Mathematics	Strongest evidence-backed reason to choose it
General intelligence	Competitive, but not clearly differentiated
Cost	Requires a workload where mathematical quality offsets the premium
Production confidence	Evidence is insufficient in the supplied research brief

Grok 4 should be tested first on math-heavy tasks, because its strongest measured result does not automatically establish broad task superiority.

A rank of 16 of 265 on the Artificial Analysis Math Index is a meaningful signal for workloads involving symbolic manipulation, quantitative reasoning, multi-step calculations, or technical explanations that depend on mathematical structure. It does not prove that Grok 4 will solve every domain problem correctly. A benchmark can identify a useful capability while leaving practical questions unanswered, including how often the model makes arithmetic slips, how it handles ambiguous prompts, and whether it explains the reasoning in a form developers can verify.

The broader ranking changes the interpretation. Grok 4 stands at 118 of 578 on the Artificial Analysis Intelligence Index. That result supports a more limited claim: Grok 4 appears capable enough to consider for general tasks, but the supplied data does not show a broad advantage over nearby models. GPT-5.5 Instant (May 2026) and LongCat 2.0 are both listed at 33.5 on that index, while GPT-5.6 Luna (low) is listed at 33.3. Grok 4 therefore needs a task-specific reason to win.

Latency is reported as 0.3 seconds to first token, while median output tokens per second is not reported. The first-token figure supports interactive testing, but it cannot establish sustained streaming performance. Developers building long answers, code generation, or batch pipelines need measurements for completion time, output stability, rate limits, retries, and concurrency. The research brief provides no verified source for these operational details, so evidence remains insufficient.

Grok 4 is economically defensible when better mathematical answers reduce downstream verification or workflow failure, but its price is hard to justify for routine general-purpose traffic.

The blended price is $6 per 1M tokens. That number matters because the model is not clearly ahead on the broad intelligence ranking. If a workload mostly involves classification, extraction, short drafting, or ordinary chat, the available evidence does not show why Grok 4 should receive a premium over less expensive nearby options.

The input and output prices also matter differently. Grok 4 charges $3 per 1M input tokens and $15 per 1M output tokens. Applications that produce long explanations, extensive code, or detailed mathematical walkthroughs will feel the output rate more strongly than applications with short responses. Developers should therefore evaluate response length as part of cost testing, not only request volume.

The comparison set includes GPT-5.6 Luna (low) at $0.45 per 1M blended tokens and LongCat 2.0 at $1.3000000000000003 per 1M blended tokens. Gemini 3 Pro Preview (low) is listed at $4.500000000000001 per 1M blended tokens. These alternatives make the value question concrete: Grok 4 needs to deliver a measurable improvement in the target workflow, especially where output tokens dominate.

The evidence does not establish whether Grok 4 reduces human review, improves task completion, or lowers retry rates. Those are the cost variables that could reverse the conclusion. Run a representative test set with identical prompts, measure accepted answers rather than raw scores, and include review time in the total cost model.

Grok 4 is worth a serious pilot for mathematical reasoning, but the supplied evidence is too incomplete for a default platform recommendation.

Choose Grok 4 when the application has a clear mathematical component and errors are expensive enough that stronger reasoning may repay the token premium. Examples include quantitative analysis, technical problem solving, formula interpretation, and developer tools that need structured mathematical explanations. The recommendation is based on Grok 4’s rank of 16 of 265 on the Artificial Analysis Math Index, not on verified claims about a specific product workflow.

Use a cheaper neighboring model first when the workload is mostly generic conversation, extraction, simple rewriting, or high-volume automation. Grok 4’s broad intelligence position, 118 of 578, does not provide enough evidence of a general advantage. The listed alternatives also create a meaningful cost test, particularly GPT-5.6 Luna (low) and LongCat 2.0.

Do not choose Grok 4 solely because the mathematics ranking is strong. The research brief found no reliable official documentation about positioning, current pricing, or limitations. It also found no usable community posts describing production behavior. Evidence is therefore insufficient for claims about coding reliability, tool calling, safety behavior, context-window performance, support, or availability.

A practical adoption path is a narrow pilot. Compare Grok 4 with one lower-cost alternative on real prompts. Score correctness, review effort, response length, latency, and failure recovery. Keep Grok 4 only if the improvement is visible in the business metric that matters. Data source: Artificial Analysis.

Grok 4 should enter production only after developers validate the unanswered operational questions that benchmarks cannot resolve.

The supplied research brief provides no verified official source and no reliable community evidence. The FAQ below separates what the data supports from what still requires direct testing.