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Comparison · 3 models · Updated Nov 2, 2026

Qwen3 Coder Flash vs Codestral 25.08 vs ERNIE 4.5 VL 424B A47B

Qwen3 Coder Flash comes out ahead, 51 to 47 and 44 on our weighted score, though Codestral 25.08 is 25% cheaper per token.

  1. Our pick

    Alibaba (Qwen)

    Qwen3 Coder Flash

    Released Jul 28, 2025

    51/100
    • ECI—
    • Price$0.30 / $1.50
    • Context1M
  2. Mistral AI

    Codestral 25.08

    Released Jul 30, 2025

    47/100
    • ECI—
    • Price$0.30 / $0.90
    • Context128K
  3. Baidu

    ERNIE 4.5 VL 424B A47B

    Released Jun 30, 2025

    44/100
    • ECI—
    • Price$0.42 / $1.25
    • Context123K
01 — Verdict

Qwen3 Coder Flash is our pick

Qwen3 Coder Flash is the better all-round choice, scoring 51/100 against Codestral 25.08 (47) and ERNIE 4.5 VL 424B A47B (44). It leads on context window. Codestral 25.08 wins on price. 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 priceCodestral 25.08Codestral 25.08 $0.45 · Qwen3 Coder Flash $0.60 · ERNIE 4.5 VL 424B A47B $0.627 per 1M tokens (3:1 blend)
  • Longest contextQwen3 Coder FlashQwen3 Coder Flash 1,000,000 · Codestral 25.08 128,000 · ERNIE 4.5 VL 424B A47B 123,000 tokens
  • Widest inputsERNIE 4.5 VL 424B A47B Qwen3 Coder Flash: Text · Codestral 25.08: Text · ERNIE 4.5 VL 424B A47B : Text, Images
  • Self-hostingERNIE 4.5 VL 424B A47B Publishes downloadable weights
How the score is built
MeasureWeightQwen3 Coder FlashCodestral 25.08ERNIE 4.5 VL 424B A47B
Price50%586457
Inputs & features30%353535
Context window20%602423
Overall100%51/10047/10044/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Qwen3 Coder Flash vs Codestral 25.08 vs ERNIE 4.5 VL 424B A47B specifications side by side
SpecificationQwen3 Coder FlashAlibaba (Qwen)Codestral 25.08Mistral AIERNIE 4.5 VL 424B A47B Baidu
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.30 (best)$0.30 (best)$0.42
Output$1.50$0.90 (best)$1.25
Cached input$0.06$0.03 (best)—
Blended (3:1)$0.60$0.45 (best)$0.627
Long-context rateOver 32K: $0.50 / $2.50Same rateSame rate
Price sourceOfficial Alibaba APIOfficial Mistral APIMedian of 1 providers
Limits
Context window1,000,000 tokens (best)128,000 tokens123,000 tokens
Max output65,536 tokens (best)8,192 tokens16,000 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoYes
Tool callingYesYesNo
Structured outputYesYesNo
Availability
WeightsProprietaryProprietaryOpen
API model IDqwen3-coder-flashcodestral-2508—
API providers1011 (best)1
ReleasedJul 28, 2025Jul 30, 2025Jun 30, 2025
Knowledge cutoffApr 2025—Mar 31, 2025
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Qwen3 Coder Flash$6.00
  • Codestral 25.08$4.80
  • ERNIE 4.5 VL 424B A47B $6.70
04 — Questions

Which should you choose?

Which is better: Qwen3 Coder Flash, Codestral 25.08 or ERNIE 4.5 VL 424B A47B ?

Qwen3 Coder Flash is the better all-round choice, scoring 51/100 against Codestral 25.08 (47) and ERNIE 4.5 VL 424B A47B (44). It leads on context window. Codestral 25.08 wins on price. 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, Qwen3 Coder Flash, Codestral 25.08 or ERNIE 4.5 VL 424B A47B ?

Codestral 25.08 is cheaper at $0.30 input / $0.90 output per million tokens (official Mistral API price). Qwen3 Coder Flash costs $0.30 input / $1.50 output per million tokens (official Alibaba API price); ERNIE 4.5 VL 424B A47B costs $0.42 input / $1.25 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.45 per million tokens for Codestral 25.08 versus $0.60 for Qwen3 Coder Flash (1.3× as much) and $0.627 for ERNIE 4.5 VL 424B A47B (1.4× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Qwen3 Coder Flash has not been scored yet, Codestral 25.08 has not been scored yet and ERNIE 4.5 VL 424B A47B has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 Coder Flash, Codestral 25.08 and ERNIE 4.5 VL 424B A47B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that ERNIE 4.5 VL 424B A47B does not support tool calling, which most coding agents need.

Which has the bigger context window?

Qwen3 Coder Flash has the largest context window at 1,000,000 tokens, against 128,000 for Codestral 25.08 and 123,000 for ERNIE 4.5 VL 424B A47B . Maximum output per response: Qwen3 Coder Flash up to 65,536, Codestral 25.08 up to 8,192, ERNIE 4.5 VL 424B A47B up to 16,000 tokens.

Which can read images, PDFs, audio or video?

Qwen3 Coder Flash accepts text; Codestral 25.08 accepts text; ERNIE 4.5 VL 424B A47B accepts text and images. ERNIE 4.5 VL 424B A47B handles the widest range of inputs.

Are any of these open source?

ERNIE 4.5 VL 424B A47B publishes its weights and can be self-hosted; Qwen3 Coder Flash and Codestral 25.08 is proprietary.

Which is newer?

Codestral 25.08 is the newest, released Jul 30, 2025. Qwen3 Coder Flash came out Jul 28, 2025; ERNIE 4.5 VL 424B A47B came out Jun 30, 2025. Knowledge cutoff: Qwen3 Coder Flash Apr 2025, ERNIE 4.5 VL 424B A47B Mar 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 Nov 2, 2026.