TL;DR
Grok 4.7 and Claude Fable 5.1 compete in the same frontier-model tier, but they optimize for different deployment economics. Grok 4.7 is positioned around coding, agentic work, and price-performance, with a 500K-token context window and official pricing starting at $2/M input and $6/M output tokens. Claude Fable 5.1 doubles the context capacity to 1M tokens and is designed for demanding reasoning and long-horizon agentic work, at $10/M input and $50/M output tokens.
The benchmark picture is mixed rather than one-sided. xAI's official launch evaluation reports Fable 5.1 ahead on CursorBench 4.0 and Terminal-Bench 4.0, while Grok 4.7 leads on DeepSWE v1.1, EEBench, and the Harvey Legal Agent Benchmark. In practice, the choice is less about a universal winner and more about cost per accepted result, task duration, context requirements, tool use, and retry behavior.
Key Takeaways
- Grok 4.7 costs $2/M input and $6/M output tokens below the higher-context pricing threshold; cached input is $0.50/M.
- Claude Fable 5.1 costs $10/M input and $50/M output tokens, with $0.25/M cache reads.
- Claude Fable 5.1 offers a 1M-token context window; Grok 4.7 offers 500K tokens.
- Benchmark leadership is task-dependent: Fable 5.1 leads several long-horizon coding tests, while Grok 4.7 leads selected engineering and domain-agent evaluations in xAI's comparison.
- The most useful production metric is cost per successful task, not price per million tokens in isolation.
What Are Grok 4.7 and Claude Fable 5.1?
Grok 4.7 Overview
Grok 4.7 is xAI's frontier model for coding, agentic tasks, and knowledge work, released on September 21, 2026. xAI says it uses a new, larger base model than Grok 4.6 and a longer reinforcement-learning run weighted toward tasks that can take many hours to complete. The release also emphasizes better self-verification and long-context management.
The official developer documentation specifies model ID grok-4.7, a 500,000-token context window, text and image input, text output, four reasoning levels—low, medium, high, and xhigh—and tools including function calling, web search, X search, and code execution.
Official Grok 4.7 launch visual - SpaceXAI
Claude Fable 5.1 Overview
Claude Fable 5.1 was released on September 1, 2026. Anthropic positions it for demanding reasoning, long-running coding, multistep research, document-heavy professional work, and agents that continue operating over extended sessions.
Anthropic's model documentation specifies a 1M-token context window, up to 128K output tokens, text and image input, adaptive thinking, and a June 2026 reliable knowledge cutoff.
Official Claude Fable 5.1 launch visual - Anthropic
Grok 4.7 vs Claude Fable 5.1 at a Glance
| Specification | Grok 4.7 | Claude Fable 5.1 |
|---|---|---|
| Release date | September 21, 2026 | September 1, 2026 |
| Provider | xAI / SpaceXAI | Anthropic |
| Model ID | grok-4.7 | claude-fable-5-1 |
| Primary positioning | Coding, agents, knowledge work | Demanding reasoning and long-horizon agents |
| Context window | 500K tokens | 1M tokens |
| Max output | No fixed text output limit documented | Up to 128K tokens |
| Input modalities | Text + image | Text + image |
| Output | Text | Text |
| Knowledge cutoff | May 2026 | June 2026 |
| Reasoning | Low / Medium / High / xhigh | Adaptive thinking + effort controls |
| Web/search tools | Web search + X search | Environment/tool dependent |
| Function/tool calling | Yes | Yes |
| Model weights | Closed | Closed |
| CursorBench 4.0 coding performance | 46.3% | 51.8% |
| DeepSWE v1.1 agent performance | 71.0% (high effort) | 70.0% |
| Terminal-Bench 4.0 agent performance | 38.0% | 57.9% |
| Typical use case | Cost-sensitive coding and web/X-connected agents | Long-horizon coding and failure-sensitive professional work |
The largest structural differences are context capacity and token economics. Grok 4.7's official API documentation confirms 500K context and $2/$6 base pricing, while Anthropic's Fable 5.1 documentation confirms 1M context and $10/$50 base pricing.
Head-to-Head Benchmark Results
The cleanest direct comparison currently comes from xAI's Grok 4.7 launch benchmark table, which reports both models in the same published evaluation.
The figures below are vendor-reported rather than independently reproduced. In xAI's published table, Grok 4.7 is evaluated at xhigh effort and Claude Fable 5.1 at max effort; xAI separately marks Grok 4.7's DeepSWE result as high effort. Use them to identify workload patterns, then validate both models on your own prompts, tools, repositories, and acceptance criteria.
| Benchmark | Grok 4.7 | Claude Fable 5.1 | Observed gap |
|---|---|---|---|
| CursorBench 4.0 | 46.3% | 51.8% | Fable +5.5 pts |
| DeepSWE v1.1 | 71.0%* | 70.0% | Grok +1.0 pt |
| AA Briefcase v1.1 | 1,657 | 1,678 | Fable +21 |
| Terminal-Bench 4.0 | 38.0% | 57.9% | Fable +19.9 pts |
| Harvey Legal Agent Benchmark | 19.6% | 6.7% | Grok +12.9 pts |
| HealthBench Professional | 56.7% | 62.1% | Fable +5.4 pts |
| EEBench | 64.0% | 56.4% | Grok +7.6 pts |
* xAI marks Grok 4.7's DeepSWE result as high effort. The broader result is task specialization rather than a universal hierarchy: Fable is stronger on several long-horizon coding and professional workflows, while Grok is stronger on several engineering and domain-agent tests in the same vendor table.
Professional Knowledge Work
In xAI's head-to-head table, Fable 5.1 slightly leads AA Briefcase v1.1, while Grok 4.7 leads EEBench and the Harvey Legal Agent Benchmark. Fable 5.1 leads HealthBench Professional. The split reinforces a simple point: knowledge work is not one capability. Engineering, medicine, law, finance, research, and office automation impose different tool and reasoning requirements.
Coding Performance
Coding is where the comparison is most nuanced. On CursorBench 4.0, Fable 5.1 reaches 51.8% versus 46.3% for Grok 4.7. On DeepSWE v1.1, Grok 4.7 reaches 71.0% versus 70.0% for Fable 5.1. The largest separation appears on Terminal-Bench 4.0, where Fable 5.1 reaches 57.9% versus Grok 4.7 at 38.0%.
| Coding dimension | Grok 4.7 | Claude Fable 5.1 |
|---|---|---|
| Repository engineering | Very strong | Very strong |
| DeepSWE | Slight lead in xAI table | Very close |
| CursorBench 4.0 | 46.3% | 51.8% |
| Terminal autonomy | Strong | Major strength |
| Long-context codebase work | 500K context | 1M context |
| Repeated-call token cost | Much lower | Premium |
| Native xAI code execution | Supported | Depends on Claude environment/tools |
| Long unattended execution | Explicit training focus | Core product positioning |
The likely deployment implication is that Fable 5.1 deserves attention for terminal-heavy, long-running coding agents, while Grok 4.7 is compelling where software-engineering quality is sufficient and token cost materially affects unit economics.
Agentic Workflows
Both models are designed for agentic workflows rather than isolated prompt-response sessions. xAI says Grok 4.7 was trained on a harder mix of longer-duration tasks and improved self-verification. Anthropic describes Fable 5.1 as a model for work that can run for hours and span many applications.
| Agent requirement | Grok 4.7 | Claude Fable 5.1 |
|---|---|---|
| Long-running reasoning | Strong | Very strong |
| Context capacity | 500K | 1M |
| Self-verification | Explicit training focus | Explicit long-horizon focus |
| Tool use | Strong | Strong |
| Search-native workflow | Web + X search | Environment dependent |
| Long repeated context | Prompt cache + compaction | 1M context + low-cost cache reads |
| Raw token cost | Lower | Higher |
Pricing and Deployment Economics
| Official base pricing | Grok 4.7 | Claude Fable 5.1 |
|---|---|---|
| Input / 1M tokens | $2 | $10 |
| Cached input / cache read | $0.50 below 200K prompt | $0.25 |
| Output / 1M tokens | $6 | $50 |
| 10M input tokens | $20 | $100 |
| 10M output tokens | $60 | $500 |
| US regional endpoint premium | +10% | Platform dependent |
At standard uncached token rates, Grok 4.7's input price is 80% lower than Fable 5.1's and its output price is 88% lower. However, Anthropic's cache-read pricing can materially reduce Fable 5.1's effective cost in repeated, agentic workloads.
Pricing caveat: Grok 4.7's $2/M input and $6/M output figures are base rates. SpaceXAI documents separate higher-context pricing for requests that exceed 200K context. The calculations below assume requests remain within the base-pricing tier and exclude tool charges, regional premiums, and cache-write costs.
Example workload: 10M input tokens + 2M output tokens.
- Grok 4.7: $20 input + $12 output = $32.
- Claude Fable 5.1: $100 input + $100 output = $200.
- Nominal gap before cache effects: $168.
The better production metric is cost per successfully completed task. A more expensive model can still be economical if it reduces retries, failures, or human correction. A cheaper model can dominate when both models pass the same acceptance test.
Context and Reasoning Controls
Fable 5.1 provides a 1M-token context window, compared with 500K tokens for Grok 4.7. That difference can matter for very large repositories, document sets, legal discovery, scientific research, or agents carrying extensive histories.
Grok 4.7 exposes low, medium, high, and xhigh reasoning settings. Fable 5.1 uses adaptive thinking with effort controls. These labels are not directly comparable, so a fair test should hold tasks and acceptance criteria constant rather than matching setting names.
Multimodal and Tool Capabilities
Both models accept text and images. Grok 4.7's API includes function calling, web search, X search, and code execution. Claude Fable 5.1 is optimized for document, spreadsheet, slide, research, and long-running agent workflows, with tool behavior depending on the Claude environment or application stack.
| Capability | Grok 4.7 | Claude Fable 5.1 |
|---|---|---|
| Text input | Yes | Yes |
| Image input | Yes | Yes |
| Function/tool calling | Yes | Yes |
| Web search | Native xAI tool | Environment dependent |
| X search | Native | No equivalent proprietary X integration |
| Code execution | Native xAI tool | Environment dependent |
| Documents / spreadsheets / slides | General knowledge-work focus | Explicit product focus |
Decision Summary
| Dimension | Grok 4.7 | Claude Fable 5.1 |
|---|---|---|
| Coding quality | Frontier | Frontier |
| CursorBench 4.0 | 46.3% | 51.8% |
| DeepSWE v1.1 | 71.0%* | 70.0% |
| Terminal-Bench 4.0 | 38.0% | 57.9% |
| EEBench | 64.0% | 56.4% |
| Harvey Legal Agent | 19.6% | 6.7% |
| HealthBench Professional | 56.7% | 62.1% |
| Context | 500K | 1M |
| Input price | $2/M | $10/M |
| Output price | $6/M | $50/M |
| Search | Web + X | Tool/environment dependent |
| Long-running agents | Strong | Major strength |
| Price-performance | Major advantage | Premium capability tier |
| Typical fit | Scale-sensitive frontier workloads | High-value long-horizon tasks |
Can You Use Grok 4.7 and Claude Fable 5.1 Through CometAPI?
Yes. Grok 4.7 API in CometAPI and Claude Fable 5.1 API in CometAPI can be used as part of a multi-model routing strategy. That matters because the best production architecture may not require choosing only one frontier model.
A practical routing pattern is:
- Default route: Grok 4.7 for cost-sensitive frontier tasks.
- Escalation route: Claude Fable 5.1 when an evaluation fails, the task exceeds context requirements, or a long-running agent needs stronger terminal execution.
This lets teams compare accepted-result rate, total tokens, latency, retries, and cost per accepted result instead of relying on one public leaderboard.
Grok 4.7 vs Claude Fable 5.1: How to choose
Choose Grok 4.7 for Cost-Sensitive and Search-Native Workloads
- High-volume coding assistants where token cost materially affects unit economics.
- Engineering or technical agents where Grok's domain results align with the workload.
- Research that benefits from native web and X search.
- Batch knowledge processing and repeated background automation.
- Workloads where both models pass the same acceptance threshold and cost becomes decisive.
For developers using a multi-model gateway, Grok 4.7 API in CometAPI can be evaluated alongside other frontier models through one integration layer.
Choose Claude Fable 5.1 for Long-Horizon and Failure-Sensitive Workloads
- Multi-hour autonomous coding and terminal-heavy workflows.
- Very large repositories or document sets that benefit from a 1M-token context window.
- Complex professional agents that must preserve state across many steps.
- High-value business workflows where retry or failure costs outweigh raw token cost.
- Research and automation tasks where Anthropic's long-horizon agent benchmarks map closely to production needs.
The Claude Fable 5.1 API in CometAPI uses model ID `claude-fable-5-1`; pricing and routing should be verified at deployment time because gateway rates can change independently of Anthropic's list price.
Conclusion
Grok 4.7 is the stronger starting point when token cost, web/X-connected tools, and scale-sensitive agent workflows dominate the decision. Claude Fable 5.1 is the stronger candidate when a 1M-token context window and demanding long-running coding or professional tasks matter more than base token price. The vendor-reported benchmark results are mixed, so neither model is a universal winner.
Before choosing, test both on the same production tasks, tools, time budget, and acceptance criteria. Compare cost per accepted result, latency, retries, tool failures, and human correction time alongside the published scores.
FAQ
How Should Teams Evaluate Grok 4.7 vs Claude Fable 5.1 Fairly?
Start with representative production tasks rather than a generic leaderboard. Use the same repository state, tool permissions, time budget, and acceptance criteria for both models. Record accepted-result rate, end-to-end latency, input and output tokens, cache behavior, tool failures, retries, and human correction time. Run enough repeated trials to separate model behavior from task variance.
When Can Grok 4.7 Cost More Than Claude Fable 5.1 per Accepted Task?
A lower token rate can become more expensive when it causes additional retries, longer prompts, failed tool calls, or more human review. Conversely, a premium model is not automatically economical: its higher completion rate must offset the added inference cost. Compare cost per accepted task, not cost per token alone.
When Should a Router Escalate from Grok 4.7 to Claude Fable 5.1?
Use measurable triggers. A cost-sensitive default route can handle tasks that pass validation quickly, while escalation can activate when a task exceeds the preferred context range, fails an automated evaluation, requires long terminal execution, or carries a high cost of error. Log the trigger and outcome so the routing policy can be tuned with production evidence.
Which Grok 4.7 vs Claude Fable 5.1 Benchmark Caveats Matter Most?
The most important caveats are benchmark version, reasoning effort, agent harness, tool access, safeguards, and whether the result is vendor-reported or independently reproduced. CursorBench 3.2.0 and 4.0, for example, should not be compared as if they were the same test. Public scores are useful for forming hypotheses, but deployment decisions should rely on controlled internal evaluations.