Model comparison
Grok 4.5 vs Grok 4.6
Two SpaceXAI tiers compared on the figures that decide which one a workload actually needs.
Catalog record checked August 12, 2026; individual provider fields may change.
SpaceXAI
Grok 4.5
Balanced
SpaceXAI
Grok 4.6
Frontier
| Specification | Grok 4.5 | Grok 4.6 |
|---|---|---|
| Provider | SpaceXAI | SpaceXAI |
| Tier | Balanced | Frontier |
| Context window | 500K | 500K |
| Max output | Not verified | Not verified |
| Input / 1M tokens | $2 | $2 |
| Output / 1M tokens | $6 | $6 |
| Weights | Closed | Closed |
| Parameters | Not disclosed | Not disclosed |
| Reasoning levels | low, medium, high | low, medium, high, xhigh |
| Modalities | text, image | text, image |
| Released | July 16, 2026 | August 12, 2026 |
| Artificial Analysis Intelligence Index [high] (2026-08-08) | 56 | Winner: 61 |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Pricing tiers: Grok 4.5: Base tier is $2/$6 per million tokens; prompts above 200K tokens are priced at $4/$12, and web/X search tool calls bill separately. · Grok 4.6: Base tier is $2/$6 per million tokens; prompts at or above 200K tokens are priced at $4/$12. Cached input is $0.50 / $1.00. Web/X search tool calls bill separately.
Grok 4.5
SpaceXAI's mid tier, priced below the frontier labs with a large context window and image input.
Best for
- Real-time data queries
- Technical tasks
- Cost-sensitive mid-tier work
Watch out
Token rates double above a 200K-token prompt, and web/X search tool calls bill separately. xAI's current code/chat default is Grok 4.6 at the same $2/$6 band.
Grok 4.6
SpaceXAI's current code and chat default — same $2/$6 list as Grok 4.5, with a 500K context window and image input.
Best for
- Coding agents
- Chat and knowledge work
- Cost-sensitive frontier work
Watch out
Token rates double above a 200K-token prompt. DeepSWE 1.1 best-effort for this family is the xhigh row at 66.7% (the catalog table rounds Pass@1 to 67%), not the higher-scoring medium config.
Benchmark
DeepSWE 1.1 in context
Both models shown against the wider field, with cost per completed task alongside the score.
Local leader
Claude Opus 5 [max]
74%
Rows shown
24
Highest published reasoning effort per model (not best Pass@1)
Snapshot date
2026-08-13
Mirrored from deepswe.datacurve.ai
Better is toward the top-right (higher pass rate, lower cost). X-axis is reversed to match DeepSWE’s public chart. v1.1 uses average cost / tokens / steps; v1 uses published medians.
| # | Model | Pass@1 | Cost / task | Tokens / task | Steps / task |
|---|---|---|---|---|---|
| 1 | Claude Opus 5 [max] | 74% | $11.84 | 118k | 99 |
| 2 | GPT-5.6 Sol [max] | 73% | $8.39 | 60k | 61 |
| 3 | Claude Fable 5 [max] | 70% | $21.63 | 119k | 88 |
| 4 | GPT-5.6 Terra [max] | 70% | $4.95 | 72k | 76 |
| 5 | Kimi K3 [max] | 69% | $4.65 | 82k | 98 |
| 6 | GPT-5.6 Luna [max] | 67% | $3.03 | 73k | 102 |
| 7 | GPT-5.5 [xhigh] | 67% | $7.23 | 46k | 82 |
| 8 | Grok 4.6 [xhigh] | 67% | $5.50 | 71k | 87 |
| 9 | Gemini 3.7 Flash [high] | 65% | $2.18 | 107k | 125 |
| 10 | DeepSeek V4-Pro [max] | 63% | $0.24 | 106k | 155 |
| 11 | Claude Opus 4.8 [max] | 59% | $13.22 | 135k | 120 |
| 12 | Qwen3.8-Max [xhigh] | 58% | $3.73 | 95k | 111 |
| 13 | Muse Spark 1.2 [xhigh] | 55% | $3.70 | 99k | 101 |
| 14 | Claude Sonnet 5 [max] | 54% | $26.40 | 214k | 268 |
| 15 | Grok 4.5 [high] | 54% | $2.42 | 36k | 61 |
| 16 | DeepSeek V4-Flash [max] | 53% | $0.10 | 108k | 153 |
| 17 | Muse Spark 1.1 [xhigh] | 53% | $2.36 | 74k | 96 |
| 18 | GPT-5.4 [xhigh] | 52% | $5.65 | 71k | 70 |
| 19 | Gemini 3.6 Flash [high] | 47% | $4.42 | 96k | 117 |
| 20 | GLM 5.2 [max] | 44% | $3.92 | 78k | 129 |
| 21 | Gemini 3.5 Flash [high] | 36% | $3.45 | 76k | 105 |
| 22 | Kimi K2.7 Code | 31% | $2.82 | 59k | 149 |
| 23 | Claude Sonnet 4.6 [high] | 30% | $5.52 | 76k | 134 |
| 24 | Gemini 3.1 Pro [high] | 12% | $2.14 | 28k | 76 |
DeepSWE “Best” picks the highest published reasoning effort per model (not the highest pass rate). Small gaps may not be statistically meaningful — confirm on deepswe.datacurve.ai.
Common questions
Grok 4.5 vs Grok 4.6
Answered from the verified figures on this page rather than general guidance.
Is Grok 4.5 or Grok 4.6 cheaper for input?
Both cost $2 per million input tokens at standard rates, so input price is not a deciding factor between them.
Is Grok 4.5 or Grok 4.6 cheaper for output?
Both cost $6 per million output tokens at standard rates, so output price is not a deciding factor between them.
Which has the larger context window, Grok 4.5 or Grok 4.6?
Both accept about 500K tokens of context, so document length will not decide between them.
Do Grok 4.5 and Grok 4.6 support the same reasoning levels?
Grok 4.5 exposes low, medium, high, while Grok 4.6 exposes low, medium, high, xhigh.
Should I use Grok 4.5 or Grok 4.6?
Grok 4.5 is the balanced tier and Grok 4.6 the frontier tier. The useful question is whether your hardest task actually fails on the cheaper one — most production volume such as classification, extraction and summarisation does not.
Next step
Choosing between them
Tier and workload decide this more reliably than a leaderboard position does.
If both sit in the same tier, the decision usually comes down to context window and output price rather than headline capability — output tokens dominate real bills.
If one is a step up within the same provider, the useful question is whether your hardest task actually fails on the cheaper tier. Most production volume — classification, extraction, summarization — does not.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Muse Code, or Lovable? Compare agentic harnesses · Latest releases.