Grok 4.8 vs Grok 4.7: Expected Upgrades, 2.5T and API Pricing

Five expected changes in Grok 4.8

1. A 2.5T base: more capacity, no published gain yet

In his 2026-09-14 post, Musk called Grok 4.8 a 2.5T model trained with a new C++ stack and said it would finish training that week and start RL. That is a historical plan, not confirmation that training or release has finished. The post does not specify active parameters, dense versus MoE architecture, or a comparable Grok 4.7 parameter count. A percentage size increase would be invented.

2. Harder reasoning and coding: fewer failed steps

The Grok 4.7 announcement already emphasizes longer reinforcement learning, multi-hour tasks and self-verification. Our expectation for 4.8 is a higher completion rate on multi-file fixes and constrained reasoning: finding the cause, applying a patch, checking it and recovering from failure. This is an editorial hypothesis based on that trajectory and Musk’s outlook; no 4.8 coding score has been published.

3. Multimodal performance: an explicitly named weakness

In another 2026-09-14 post, Musk wrote “We need to fix multimodal performance” and “Grok 4.8 will be a noticeable improvement.” Reading charts, screenshots and document layouts is therefore a valuable comparison angle. He did not promise a particular 4.8 vision score or native audio/video API. His Opus 5.0 comparison is an opinion, not a controlled benchmark; the Astra/Fable remark refers to 4.9.

4. C++ training efficiency: not an API speed guarantee

A training stack determines how a model is trained. It does not establish the deployed inference stack, time to first token or output tokens per second. Better training efficiency could support more experiments or training work within a budget; whether developers receive faster or cheaper inference remains unknown. Do not turn “new C++ stack” into “4.8 is twice as fast.”

5. Long tasks: better use of context matters as much as size

Grok 4.7 has a documented 500K-token context window. Grok 4.8’s window has not been announced. A useful upgrade would retain constraints and evidence across long agent runs with fewer human corrections, even at the same context length. A new model does not automatically know live events: current web or X information still requires the relevant search tools, and route support must be checked.

Grok 4.7 benchmarks: a real baseline for the comparison

The official 2026-09-21 table reports the following. Grok 4.7 uses xHigh effort unless noted; Grok 4.6 uses High. These are vendor results under the published harness settings, not an independent 4.8 comparison. There are no published Grok 4.8 scores to fill in.

*DeepSWE: Grok 4.7 High.

Three tests that would make an improvement visible

These are proposed evaluations, not demos of an unreleased model. Save the same inputs, tool access, token/time budget and grading rules for both models; repeat tasks and report failures as well as successes.

Multi-file coding: Give each model the same repository commit and failing regression test: “Fix duplicate billing when a timed-out request is retried; preserve successful retry behavior; add a regression case.” Grade hidden tests, patch scope, tool calls, human interventions and total cost. A coherent patch that passes checks is the visible result.

Verifiable reasoning: Provide a 12-job scheduling problem with dependencies, durations, deadlines and two machines. Require a machine-readable schedule plus a checker. Grade constraint violations and completion time against a known feasible solution; never award a win for a longer explanation alone.

Documents and images: Supply the same financial report, chart image and an amended table with one contradictory figure. Ask for the correct number, page/row citations and a reconciliation. Grade numeric accuracy and evidence grounding. Use a shared text length within 4.7’s supported window and routes that accept the same image inputs.

Grok 4.8 vs Grok 4.7 API pricing: compare cost per accepted task

Grok 4.8 pricing is unknown. The $2 input / $6 output official rate belongs to Grok 4.7, which launched at the same headline price as 4.6. On 2026-10-29, both the 4.7 card and 4.6 card span $0.1191–$1.1212 input / $0.3574–$3.3636 output per 1M tokens. At 100K input plus 20K output, that is $0.32 at the official 4.7 rate versus about $0.0191 at the lowest checked route, excluding tools, caching and retries. A stronger model can cost less per accepted task if it needs fewer retries; it can also cost more if it spends more reasoning tokens. No 4.8 savings can yet be calculated.

Run the Grok 4.7 baseline now

Register, create an API key, and use grok-4.7 at https://apimaster.ai/v1. Keep the model configurable for a later controlled comparison. The example calls the available model; image and tool support depend on the selected route.

import os
from openai import OpenAI

client = OpenAI(api_key=os.environ["APIMASTER_API_KEY"], base_url="https://apimaster.ai/v1")
response = client.chat.completions.create(
    model="grok-4.7",
    messages=[{"role": "user", "content": "Explain how to test duplicate billing when a timed-out request is retried. Return concrete regression cases."}],
)
print(response.choices[0].message.content)

FAQ

Has Grok 4.8 been released?

No public release was verified in the official catalog or release notes on 2026-10-29. The September training plan is not a launch announcement.

Will Grok 4.8 be better than Grok 4.7?

Musk expects a noticeable improvement. Harder coding, reasoning and multimodal tasks are useful evaluation targets, but there is no published head-to-head score yet.

Will Grok 4.8 be faster or have a larger context window?

Neither is confirmed. The C++ statement concerns training; 500K context is the documented 4.7 baseline.

Can I call grok-4.8 on APIMaster?

There were 0 public routes at this check. Use grok-4.7 for the baseline and check the 4.8 card for availability. No advance token price is promised.

Sources and verification date

2026-10-29. xAI: Grok 4.7 · xAI models · xAI release notes · Musk: 2.5T / C++ / RL · Musk: multimodal / 4.8

APIMaster: grok-4.8 · grok-4.7 · grok-4.6

For release-date updates, see the Grok 4.8 API status guide. For the released model, see the Grok 4.7 API guide.

Register, create an API key, and use grok-4.7 at https://apimaster.ai/v1. Keep the model configurable for a later controlled comparison. The example calls the available model; image and tool support depend on the selected route. grok-4.7 · Up to ~94% off