Budget models are useful when their lower token price survives retries, long outputs, and human review. The relevant metric is cost per successful task, not the cheapest input row.
Current Shortlist
| Model | Input / output per 1M | Context | Current role |
|---|---|---|---|
| Kimi K2.7 Code | $0.95 cache miss, $0.19 cache hit / $4.00 | 256K | Cheaper routine Kimi coding API lane |
| Gemini 3 Flash | $0.50 / $3.00 | ~1M | Gemini high-context value lane |
| MiniMax M3 | Standard PAYG starts at $0.60 / $2.40 | 1M | Coding-agent value lane to test |
| Xiaomi MiMo-V2.5 | Overseas list starts at $0.14 / $0.28 | 1M | Low-cost long-context and open-weight evaluation lane |
| GPT-5.6 Luna | $1.00 / $6.00 | Not published | Restricted preview; not a public budget recommendation |
Subscription and Token Plan quotas are not API prices. Compare them separately and verify checkout before purchase.
Best Starting Points
Kimi K2.7 Code
Use K2.7 Code for lower-cost Kimi coding searches. Moonshot documents base and HighSpeed IDs, 256K context, required thinking mode, multimodal input, and automatic context caching. Use Kimi K3 for newest-Kimi, 1M-context, or K3 benchmark intent.
Kimi’s published improvements over K2.6 are vendor evidence. AIHackers has not verified a normalized independent K2.7 coding score or run a controlled repository comparison.
Gemini 3 Flash
Use Gemini when its API or Vertex AI route, context size, and tool support fit. Verify the current model stage, regional availability, and exact free/paid rates; preview and free-tier limits can change faster than this page.
MiniMax M3 and Xiaomi MiMo
Both are newer low-cost, long-context lanes worth testing. Their strongest coding claims are vendor-reported, so require the same real repository tasks and pass conditions used for Kimi, GLM, or Claude.
GPT-5.6 Luna
Luna has a budget-looking list price, but it is available only to selected API organizations and Codex workspaces during the GPT-5.6 preview. Do not call it the best public budget model or promise ChatGPT access.
Evidence Table
benchmark artifact
Budget and Value Model Evidence
| Model | Provider | Status | Context | Input price | Output price | Coding signal | Tool-use signal | Benchmark evidence | Speed | Verdict | Sources | Checked |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Kimi K2.7 Code | Moonshot AI | active Cheaper routine Kimi coding API lane; HighSpeed is the same model at higher token prices. | 256K | $0.95 / 1M | $4.00 / 1M | Kimi K2.7 Code remains the lower-cost 256K coding lane after K3; independent normalized benchmarks are not imported. | OpenAI-compatible API; thinking mode required in the documented K2.7 Code quickstart. |
| HighSpeed model ID exists at a higher token price; latency not independently measured here. | Cheaper routine Kimi coding API lane when Kimi routing fits and 256K context is enough. | Kimi K2.7 Code quickstart [archive], Kimi K2.7 Code pricing [archive], Kimi Code K2.7 release notes [archive], SWE-bench, Berkeley Function Calling Leaderboard | 2026-06-28 |
| Gemini 3 Flash | active Current Gemini value lane where Gemini API or Vertex AI fits. | 1.05M input | $0.50 / 1M | $3.00 / 1M | not verified | Function calling and code execution supported. | not verified | Preview model positioned for lower latency; independent value not imported. | High-context value lane when Gemini API or Vertex AI fits. | Gemini API models, Gemini API pricing, Artificial Analysis: Gemini 3 Flash, LMArena leaderboard dataset | 2026-05-26 | |
| GLM-5.2 | Z.AI | active Current Z.AI flagship coding model and supported-tool value lane. | 1M | $1.40 / 1M | $4.40 / 1M | Z.AI reports 62.1 on SWE-Bench Pro and 81.0 on Terminal-Bench 2.1. | Supported-tool coding lane; BFCL score not imported. |
| Artificial Analysis flags higher output-token use; measure total cost per successful task. | July value pick to test for supported coding-tool workflows; keep Opus/GPT for final arbitration until local evals pass. | Z.AI GLM-5.2 overview [archive], Z.AI pricing [archive], Artificial Analysis: GLM-5.2 article [archive], Artificial Analysis Intelligence Index v4.1, SWE-bench, Berkeley Function Calling Leaderboard | 2026-06-28 |
| GPT-5.6 Luna | OpenAI | preview Same selected-organization API/Codex preview gate as Sol; not in ChatGPT. | not published | $1.00 / 1M | $6.00 / 1M | OpenAI positions Luna as the fastest and lowest-cost GPT-5.6 tier; independent coding quality is not verified. | API and Codex preview only. |
| Vendor-positioned as fastest; measured production latency is not verified. | Restricted-preview low-cost tier; do not present it as a public budget default. | OpenAI GPT-5.6 launch [archive], OpenAI GPT-5.6 preview access [archive], OpenAI GPT-5.6 Preview system card [archive] | 2026-06-28 |
GPT-5.6 Luna is included as preview context, not an active recommendation. Missing local quality, latency, and cost-per-successful-task results remain not verified.
GLM-5.2 sits above the strict $1 input threshold at $1.40, but it is the relevant value comparison because it adds 1M context and independent Artificial Analysis evidence.
What Not to Compare Directly
- SWE-bench Verified and SWE-Bench Pro.
- A vendor’s internal preference test and an independent aggregate index.
- Base API price and a monthly coding-plan quota.
- Cache-hit price and uncached first-run price.
- A model’s context limit and its ability to use that context accurately.
Do not claim one model delivers a percentage of another model’s total capability from a single benchmark.
Repository Test
Run each accessible model on:
| Task | Pass condition |
|---|---|
| Repository map | Correct modules and commands; no invented files |
| Bug fix | Minimal patch and relevant passing tests |
| Refactor | Preserved behavior and repository conventions |
| Review | Concrete file-grounded findings |
Record exact model ID, settings, prompt, tokens, cache behavior, retries, latency, accepted patch, and review time. Models that are inaccessible or provider-managed should be labeled accordingly rather than assigned estimated results.
Historical Budget Context
Kimi K2.5 remains useful for older free-hosting and integration searches. Kimi K2.6 remains relevant for compatible non-thinking and multimodal workflows. Neither should replace K3 for newest-Kimi intent or K2.7 Code for cheaper Kimi coding.
Older access pages can retain K2.5 when that exact hosted model is still offered. They must not describe it as Kimi’s latest coding model.
Verdict
- Start with Kimi K2.7 Code when Kimi’s API and 256K context fit.
- Test GLM-5.2 when 1M context and independent shortlist evidence justify slightly higher input pricing.
- Evaluate Gemini 3 Flash, MiniMax M3, or Xiaomi MiMo when their provider/tool route fits.
- Keep GPT-5.6 Luna in the preview watchlist until broad access exists.
- Escalate to Opus 4.8 only when a premium second pass materially improves the outcome.
Sources
- Kimi: K2.7 Code quickstart and pricing
- Z.AI: GLM-5.2 and pricing
- Google: Gemini models and pricing
- OpenAI: GPT-5.6 preview access
- Artificial Analysis: GLM-5.2
Related links
- /models/kimi-k2.7-code/
- /models/kimi-k3/
- /models/glm-5.2/
- /models/gpt-5-6/
- /compare/models/mid-range/
- /value/free-stack/
Last verified: July 18, 2026. Prices, model stages, cache terms, open-weight status, and free routes can change independently.