Command A Plus vs GPT-5.3 Codex Spark vs Qwen3.8 Max Preview
Qwen3.8 Max Preview comes out ahead, 47 to 38 and 35 on our weighted score, and it is the cheaper option too.
Cohere
Command A Plus
35/100- ECI—
- Price$2.50 / $10.00
- Context128K
OpenAI
GPT-5.3 Codex Spark
38/100- ECI—
- Price$1.75 / $14.00
- Context128K
- Our pick
Alibaba (Qwen)
Qwen3.8 Max Preview
47/100- ECI—
- Price$2.00 / $6.00
- Context1M
Qwen3.8 Max Preview is our pick
Qwen3.8 Max Preview is the better all-round choice, scoring 47/100 against GPT-5.3 Codex Spark (38) and Command A Plus (35). It leads on price and context window. GPT-5.3 Codex Spark wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceQwen3.8 Max PreviewQwen3.8 Max Preview $3.00 · Command A Plus $4.38 · GPT-5.3 Codex Spark $4.81 per 1M tokens (3:1 blend)
- Longest contextQwen3.8 Max PreviewQwen3.8 Max Preview 1,000,000 · Command A Plus 128,000 · GPT-5.3 Codex Spark 128,000 tokens
- Widest inputsGPT-5.3 Codex Spark and Qwen3.8 Max PreviewCommand A Plus: Text, Images · GPT-5.3 Codex Spark: Text, Images, PDFs · Qwen3.8 Max Preview: Text, Images, Video
- Self-hostingCommand A PlusPublishes downloadable weights
| Measure | Weight | Command A Plus | GPT-5.3 Codex Spark | Qwen3.8 Max Preview |
|---|---|---|---|---|
| Price | 50% | 19 | 18 | 27 |
| Inputs & features | 30% | 70 | 80 | 70 |
| Context window | 20% | 24 | 24 | 60 |
| Overall | 100% | 35/100 | 38/100 | 47/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.50 | $1.75 (best) | $2.00 |
| Output | $10.00 | $14.00 | $6.00 (best) |
| Cached input | — | $0.175 | — |
| Blended (3:1) | $4.38 | $4.81 | $3.00 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Cohere API | Official OpenAI API | Median of 6 providers |
| Limits | |||
| Context window | 128,000 tokens | 128,000 tokens | 1,000,000 tokens (best) |
| Max output | 64,000 tokens | 32,000 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | Yeslow · medium · high · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | command-a-plus-05-2026 | gpt-5.3-codex-spark | — |
| API providers | 1 | 1 | 6 (best) |
| Released | May 20, 2026 | Feb 5, 2026 | Jul 19, 2026 |
| Knowledge cutoff | Apr 1, 2025 | 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.
Command A Plus$45.00
GPT-5.3 Codex Spark$45.50
Qwen3.8 Max Preview$32.00
Which should you choose?
Which is better: Command A Plus, GPT-5.3 Codex Spark or Qwen3.8 Max Preview?
Qwen3.8 Max Preview is the better all-round choice, scoring 47/100 against GPT-5.3 Codex Spark (38) and Command A Plus (35). It leads on price and context window. GPT-5.3 Codex Spark wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Command A Plus, GPT-5.3 Codex Spark or Qwen3.8 Max Preview?
Qwen3.8 Max Preview is cheaper at $2.00 input / $6.00 output per million tokens (median across 6 API providers). Command A Plus costs $2.50 input / $10.00 output per million tokens (official Cohere API price); GPT-5.3 Codex Spark 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 Qwen3.8 Max Preview versus $4.38 for Command A Plus (1.5× as much) and $4.81 for GPT-5.3 Codex Spark (1.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Command A Plus has not been scored yet, GPT-5.3 Codex Spark has not been scored yet and Qwen3.8 Max Preview has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Command A Plus, GPT-5.3 Codex Spark and Qwen3.8 Max Preview yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3.8 Max Preview has the largest context window at 1,000,000 tokens, against 128,000 for Command A Plus and 128,000 for GPT-5.3 Codex Spark. Maximum output per response: Command A Plus up to 64,000, GPT-5.3 Codex Spark up to 32,000, Qwen3.8 Max Preview up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Command A Plus accepts text and images; GPT-5.3 Codex Spark accepts text, images and PDFs; Qwen3.8 Max Preview accepts text, images and video. GPT-5.3 Codex Spark handles the widest range of inputs.
Are any of these open source?
Command A Plus publishes its weights and can be self-hosted; GPT-5.3 Codex Spark and Qwen3.8 Max Preview is proprietary.
Which is newer?
Qwen3.8 Max Preview is the newest, released Jul 19, 2026. Command A Plus came out May 20, 2026; GPT-5.3 Codex Spark came out Feb 5, 2026. Knowledge cutoff: Command A Plus Apr 1, 2025, GPT-5.3 Codex Spark 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.