x-ai
SpaceXAI: Grok 4.6 (batch)
x-ai/grok-4.6:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter's catalog describes x-ai/grok-4.6:batch as a SpaceXAI Grok 4.6 variant for batch-oriented access, with text, image, and file inputs producing text. The listing reports a large context window, mandatory reasoning with selectable effort levels, tool calls, structured outputs, and response controls. It also includes design-arena and Artificial Analysis benchmark entries covering coding, agentic work, and other generation tasks. Evidence is catalog-only; an independent model card was not available in this source pack.[1]
Strengths
- Catalog-reported multimodal inputs accept text, images, and files while producing text outputs.[1]
- The catalog reports mandatory reasoning with multiple selectable effort levels and support for tools, structured outputs, seeds, and sampling controls.[1]
- Catalog-linked benchmark results cover coding, agentic, visual, document, and application-generation tasks, giving broad measured task coverage.[1]
Limitations
- Only OpenRouter catalog evidence was supplied; an independent model card, release notes, license terms, and hardware requirements were unavailable.[1]
- Benchmark coverage is limited to the listed design-arena and Artificial Analysis results and may not predict a specific production workload; validate latency, cost, quality, and safety before adoption.[1]
- The supplied evidence does not document batch throughput, availability, or retention behavior beyond the catalog listing.[1]
Where to use it
- Potentially evaluate for batch coding, knowledge-work, and STEM assistance because the catalog description cites performance in those areas.[1]
- Potentially evaluate for applications that combine text prompts with image or file inputs and need structured or tool-assisted text outputs.[1]
- Potentially evaluate for batch-oriented workflows where agentic or application-generation behavior is relevant, while verifying the exact serving behavior.[1]
Sources
- [1] OpenRouter catalog · SpaceXAI: Grok 4.6 (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Grok 4.6 is a model from SpaceXAI with frontier performance on coding, knowledge work, and STEM. It is succeeded by [Grok 4.7](/x-ai/grok-4.7).
Specifications
- Model ID
- x-ai/grok-4.6:batch
- Canonical ID
- x-ai/grok-4.6-20260810
- Creator
- x-ai
- Added to OpenRouter
- 12.08.2026
- Context length
- 500,000
- Modality
- text+image+file->text
- Input modalities
- text, image, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $1.6 / out $4.8
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | BB — next 30% of the cohort | reasoning: mandatory · default high · efforts: xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | SS — top 10% of the cohort | — |
| Agents | SS — top 10% of the cohort | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · default high · efforts: xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Intelligence index | 31 | BB — next 30% of the cohort | 13.11.2026 |
| Artificial Analysis | Coding index | 75.9 | SS — top 10% of the cohort | 13.11.2026 |
| Artificial Analysis | Agentic index | 52.5 | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | agents · agenticgamedevwin rate 47.2% · rank 10 | 1,157Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · androidnativewin rate 61% · rank 3 | 1,280Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | agents · blender3dwin rate 42.9% · rank 10 | 1,148Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · codetovideowin rate 47.3% · rank 13 | 1,140Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · fullstackwin rate 54.7% · rank 9 | 1,242Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · godotgamedevwin rate 53.2% · rank 4 | 1,256Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | agents · htmlslideswin rate 60% · rank 6 | 1,144Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · mobileappswin rate 54.9% · rank 13 | 1,226Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · pdfwin rate 59.3% · rank 10 | 1,237Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · python-pptxslideswin rate 52.8% · rank 12 | 1,200Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · spreadsheetwin rate 52.8% · rank 14 | 1,168Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · webappswin rate 55.5% · rank 14 | 1,231Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · 3dwin rate 51.8% · rank 29 | 1,257Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · asciiartwin rate 56.8% · rank 13 | 1,268Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 51.9% · rank 22 | 1,281Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · datavizwin rate 51.5% · rank 17 | 1,282Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 53% · rank 23 | 1,282Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · svgwin rate 47.6% · rank 23 | 1,221Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 52.6% · rank 25 | 1,285Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · websitewin rate 51.4% · rank 26 | 1,278Elo | AA — next 20% of the cohort | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| xAI | 500,000 | $1.6 | $4.8 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.