x-ai
SpaceXAI: Grok 4.7 (batch)
x-ai/grok-4.7:batch
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to OpenRouter's catalog entry for x-ai/grok-4.7:batch, this Grok 4.7 variant is presented as a flagship model for coding, agentic work, and knowledge tasks. It accepts text, image, and file inputs and returns text, with a 500,000-token context window. Reasoning is mandatory, enabled by default at high effort, with xhigh, high, medium, and low settings listed. The catalog also reports tools, structured outputs, and other generation controls; benchmark evidence is catalog-reported rather than independently validated.[1]
Strengths
- The OpenRouter description positions it for coding, agentic tasks, knowledge work, long-running software engineering, and checking its own work.[1]
- It combines text, image, and file inputs with text output and a large 500,000-token context window.[1]
- Cataloged controls include reasoning effort, tools, structured outputs, response formatting, seed, sampling, and token limits.[1]
Limitations
- The source pack contains only the OpenRouter catalog; an independent model card was not available, so capabilities should be validated on the intended workload.[1]
- It emits text only, and reasoning is mandatory even though its effort level can be adjusted.[1]
- The catalog leaves the knowledge cutoff unspecified, provides no Hugging Face identifier, and lacks coding and agentic index values.[1]
Where to use it
- Consider evaluating it for long-running or long-context software engineering and agentic coding workflows.[1]
- It may suit multimodal analysis tasks where text, images, or supported files must produce a textual answer.[1]
- Test it for applications that require tool use, structured responses, or explicit control over reasoning effort.[1]
Sources
- [1] OpenRouter catalog · SpaceXAI: Grok 4.7 (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Grok 4.7 is SpaceXAI's flagship model for coding, agentic tasks, and knowledge work, succeeding Grok 4.6. It is particularly strong at long-running software engineering tasks, verifying its own work, and...
Specifications
- Model ID
- x-ai/grok-4.7:batch
- Canonical ID
- x-ai/grok-4.7-20260916
- Creator
- x-ai
- Added to OpenRouter
- 21.09.2026
- 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 | AA — next 20% of the cohort | reasoning: mandatory · default high · efforts: xhigh, high, medium, low · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | No measurement | — |
| Agents | No measurement | 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 | 35.5 | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · blender3dwin rate 60% · rank 7 | 1,163Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · codetovideowin rate 42.2% · rank 18 | 1,109Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · mobileappswin rate 54.2% · rank 9 | 1,252Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · pdfwin rate 48.3% · rank 20 | 1,167Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · 3dwin rate 47.7% · rank 25 | 1,259Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 47.5% · rank 31 | 1,267Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · datavizwin rate 44.5% · rank 47 | 1,224Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 50.6% · rank 18 | 1,308Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · svgwin rate 50.6% · rank 16 | 1,270Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 49% · rank 31 | 1,274Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · websitewin rate 45.6% · rank 48 | 1,245Elo | BB — next 30% 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.