Grok 4.6 vs GPT-5.3 Codex vs Qwen3.8 Max
Qwen3.8 Max comes out ahead, 69 to 65 and 64 on our weighted score.
xAIGrok 4.6
65/100- ECI156.6
- Price$2.00 / $6.00
- Context500K
OpenAIGPT-5.3 Codex
64/100- ECI156.8
- Price$1.75 / $14.00
- Context400K
- Our pick
Alibaba (Qwen)Qwen3.8 Max
69/100- ECI156.6
- Price$2.00 / $6.00
- Context1M
Qwen3.8 Max is our pick
Qwen3.8 Max is the better all-round choice, scoring 69/100 against Grok 4.6 (65) and GPT-5.3 Codex (64). It leads on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.3 CodexCapabilities Index (ECI): GPT-5.3 Codex 156.8 · Grok 4.6 156.6 · Qwen3.8 Max 156.6
- Lowest priceGrok 4.6 and Qwen3.8 MaxGrok 4.6 $3.00 · Qwen3.8 Max $3.00 · GPT-5.3 Codex $4.81 per 1M tokens (3:1 blend)
- Longest contextQwen3.8 MaxQwen3.8 Max 1,000,000 · Grok 4.6 500,000 · GPT-5.3 Codex 400,000 tokens
- Widest inputsQwen3.8 MaxGrok 4.6: Text, Images · GPT-5.3 Codex: Text, Images, PDFs · Qwen3.8 Max: Text, Images, PDFs, Video
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Grok 4.6 | GPT-5.3 Codex | Qwen3.8 Max |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 86 | 87 | 86 |
| Price | 25% | 27 | 18 | 27 |
| Inputs & features | 15% | 70 | 80 | 90 |
| Context window | 10% | 48 | 44 | 60 |
| Overall | 100% | 65/100 | 64/100 | 69/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Grok 4.6xAI | GPT-5.3 CodexOpenAI | Qwen3.8 MaxAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.6 | 156.8 (best) | 156.6 |
| ECI rank | #19 of 148 | #18 of 148 (best) | #20 of 148 |
| GPQA DiamondGraduate-level science questions | 94.0% (best) | — | 92.7% |
| FrontierMath Tiers 1–3Research-level mathematics | 66.0% | — | 74.7% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 99.2% | — | 99.4% (best) |
| SWE-bench VerifiedFixing real GitHub issues | — | 74.8% | — |
| SimpleQA VerifiedShort factual questions | 49.3% (best) | — | 45.8% |
| Price per million tokens | |||
| Input | $2.00 | $1.75 (best) | $2.00 |
| Output | $6.00 (best) | $14.00 | $6.00 (best) |
| Cached input | $0.50 | $0.175 (best) | $0.25 |
| Blended (3:1) | $3.00 (best) | $4.81 | $3.00 (best) |
| Long-context rate | Over 200K: $4.00 / $12.00 | Same rate | Same rate |
| Price source | Official xAI API | Official OpenAI API | Official Alibaba API |
| Limits | |||
| Context window | 500,000 tokens | 400,000 tokens | 1,000,000 tokens (best) |
| Max output | 500,000 tokens (best) | 128,000 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yeslow · medium · high · xhigh | Yeslow · medium · high · xhigh | Yeslow · medium · xhigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | grok-4.6 | gpt-5.3-codex | qwen3.8-max |
| API providers | 29 (best) | 19 | 25 |
| Released | Aug 12, 2026 | Feb 5, 2026 | Aug 3, 2026 |
| Knowledge cutoff | Feb 1, 2026 | Aug 31, 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Grok 4.6$32.00
- GPT-5.3 Codex$45.50
- Qwen3.8 Max$32.00
Which should you choose?
Which is better: Grok 4.6, GPT-5.3 Codex or Qwen3.8 Max?
Qwen3.8 Max is the better all-round choice, scoring 69/100 against Grok 4.6 (65) and GPT-5.3 Codex (64). It leads on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Grok 4.6, GPT-5.3 Codex or Qwen3.8 Max?
Grok 4.6 is cheaper at $2.00 input / $6.00 output per million tokens (official xAI API price). Qwen3.8 Max costs $2.00 input / $6.00 output per million tokens (official Alibaba API price); GPT-5.3 Codex costs $1.75 input / $14.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Grok 4.6 versus $3.00 for Qwen3.8 Max (1× as much) and $4.81 for GPT-5.3 Codex (1.6× as much).
Which scores higher on benchmarks?
GPT-5.3 Codex scores higher on the Capabilities Index (ECI): GPT-5.3 Codex 156.8 (#18 of 148), Grok 4.6 156.6 (#19 of 148) and Qwen3.8 Max 156.6 (#20 of 148). The confidence ranges of the top two overlap (153.5–160.8 vs 154.7–158.9), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Grok 4.6 and Qwen3.8 Max yet, so there is no like-for-like coding score. On overall capability, GPT-5.3 Codex leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.8 Max has the largest context window at 1,000,000 tokens, against 500,000 for Grok 4.6 and 400,000 for GPT-5.3 Codex. Maximum output per response: Grok 4.6 up to 500,000, GPT-5.3 Codex up to 128,000, Qwen3.8 Max up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Grok 4.6 accepts text and images; GPT-5.3 Codex accepts text, images and PDFs; Qwen3.8 Max accepts text, images, PDFs and video. Qwen3.8 Max handles the widest range of inputs.
Are any of these open source?
No. Grok 4.6, GPT-5.3 Codex and Qwen3.8 Max are proprietary and only available through APIs and apps.
Which is newer?
Grok 4.6 is the newest, released Aug 12, 2026. Qwen3.8 Max came out Aug 3, 2026; GPT-5.3 Codex came out Feb 5, 2026. Knowledge cutoff: Grok 4.6 Feb 1, 2026, GPT-5.3 Codex Aug 31, 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
